Cure Model Regression
cureit.RdCure Model Regression
Usage
# S3 method for formula
cureit(
surv_formula,
cure_formula,
data,
conf.level = 0.95,
nboot = 100,
eps = 1e-07,
...
)
cureit(object, ...)
# S3 method for default
cureit(object, ...)Arguments
- surv_formula
formula with
Surv()on LHS and covariates on RHS.- cure_formula
formula with covariates for cure fraction on RHS
- data
data frame
- conf.level
confidence level. Default is 0.95.
- nboot
number of bootstrap samples used for inference.
- eps
convergence criterion for the EM algorithm.
- ...
passed to methods
- object
input object
See also
Other cureit() functions:
Brier_inference_bootstrap(),
broom_methods_cureit,
nomogram(),
predict.cureit()
Examples
cureit(surv_formula = Surv(ttdeath, death) ~ age + grade,
cure_formula = ~ age + grade, data = trial)
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002616112 0.569504769 0.345883977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.575003030 0.009813492 0.108542405
#> grade_iii, Cure model
#> 0.823899189
#>
#> $surv_formula
#> Surv(ttdeath, death) ~ age + grade
#> <environment: 0x55e42b372ba0>
#>
#> $cure_formula
#> ~age + grade
#> <environment: 0x55e42b372ba0>
#>
#> $data
#> # A tibble: 200 × 8
#> trt age marker stage grade response death ttdeath
#> <chr> <dbl> <dbl> <fct> <fct> <int> <dbl> <dbl>
#> 1 Drug A 23 0.16 T1 II 0 0 24
#> 2 Drug B 9 1.11 T2 I 1 0 24
#> 3 Drug A 31 0.277 T1 II 0 0 24
#> 4 Drug A NA 2.07 T3 III 1 1 17.6
#> 5 Drug A 51 2.77 T4 III 1 1 16.4
#> 6 Drug B 39 0.613 T4 I 0 1 15.6
#> 7 Drug A 37 0.354 T1 II 0 0 24
#> 8 Drug A 32 1.74 T1 I 0 1 18.4
#> 9 Drug A 31 0.144 T1 II 0 0 24
#> 10 Drug B 34 0.205 T3 I 0 1 10.5
#> # … with 190 more rows
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> $surv_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $cure_xlevels
#> $cure_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 7
#> term estimate std.error statistic conf.low conf.h…¹ p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.575 0.502 -1.15 -1.56 0.409 0.252
#> 2 age, Cure model 0.00981 0.00977 1.00 -0.00934 0.0290 0.315
#> 3 grade_ii, Cure model 0.109 0.348 0.312 -0.573 0.790 0.755
#> 4 grade_iii, Cure model 0.824 0.360 2.29 0.118 1.53 0.0222
#> # … with abbreviated variable name ¹conf.high
#>
#> $tidy$df_surv
#> # A tibble: 3 × 7
#> term estimate std.error statistic conf.…¹ conf.…² p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00262 0.00934 -0.280 -0.0209 0.0157 0.779
#> 2 grade_ii, Survival model 0.570 0.266 2.14 0.0489 1.09 0.0320
#> 3 grade_iii, Survival model 0.346 0.247 1.40 -0.139 0.831 0.162
#> # … with abbreviated variable names ¹conf.low, ²conf.high
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003 0.009813 0.108542 0.823899
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003030 0.009813492 0.108542405 0.823899189
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002616112 0.569504769 0.345883977
#>
#> $b_var
#> [1] 0.2520689112 0.0000954714 0.1207777292 0.1297791855
#>
#> $b_sd
#> [1] 0.502064648 0.009770947 0.347530904 0.360248783
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1452769 1.0043543 0.3123245 2.2870284
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.25209448 0.31520787 0.75479395 0.02219417
#>
#> $beta_var
#> [1] 8.717729e-05 7.054653e-02 6.117346e-02
#>
#> $beta_sd
#> [1] 0.009336878 0.265605964 0.247332690
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.2801913 2.1441716 1.3984564
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.77933075 0.03201914 0.16197606
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.000000000 0.000000000 0.000000000 0.604678067 0.658063410 0.000000000
#> [7] 0.417229340 0.000000000 0.879376354 0.000000000 0.000000000 0.744886187
#> [13] 0.787600867 0.142672058 0.944518547 0.000000000 0.693100768 0.000000000
#> [19] 0.000000000 0.000000000 0.000000000 0.540871173 0.006912639 0.976381134
#> [25] 0.640373656 0.000000000 0.000000000 0.684419417 0.522291631 0.000000000
#> [31] 0.278243702 0.000000000 0.000000000 0.000000000 0.246976530 0.821307758
#> [37] 0.000000000 0.666890646 0.466018936 0.456394953 0.829660071 0.854634203
#> [43] 0.000000000 0.531599829 0.000000000 0.000000000 0.000000000 0.846335953
#> [49] 0.446649365 0.887603756 0.000000000 0.000000000 0.368370905 0.837991986
#> [55] 0.736284601 0.368370905 0.762052697 0.904005497 0.000000000 0.130947018
#> [61] 0.000000000 0.000000000 0.178167087 0.000000000 0.298558895 0.093531067
#> [67] 0.960518552 0.000000000 0.000000000 0.000000000 0.000000000 0.387858887
#> [73] 0.968455884 0.020860827 0.613665875 0.000000000 0.753465281 0.000000000
#> [79] 0.000000000 0.000000000 0.586773524 0.036370054 0.000000000 0.427038837
#> [85] 0.267747949 0.984266892 0.106209363 0.895813391 0.000000000 0.000000000
#> [91] 0.727657186 0.397671772 0.000000000 0.246976530 0.631469660 0.920311545
#> [97] 0.000000000 0.000000000 0.000000000 0.348502061 0.550166021 0.862915985
#> [103] 0.436874482 0.000000000 0.494318881 0.513013956 0.000000000 0.118522726
#> [109] 0.000000000 0.503694197 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.779118376 0.649247645 0.000000000 0.992139734 0.308649170
#> [121] 0.080274841 0.568542449 0.000000000 0.000000000 0.718999352 0.475516896
#> [127] 0.000000000 0.201867710 0.000000000 0.000000000 0.224987874 0.796088245
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.912176411 0.000000000
#> [139] 0.000000000 0.000000000 0.952539418 0.318644852 0.000000000 0.000000000
#> [145] 0.236117909 0.804529313 0.770582430 0.000000000 0.701722215 0.328677697
#> [151] 0.871155498 0.000000000 0.000000000 0.000000000 0.000000000 0.065734870
#> [157] 0.000000000 0.338572747 0.675684959 0.050684149 0.154512416 0.358472658
#> [163] 0.559374570 0.000000000 0.000000000 0.000000000 0.189977968 0.000000000
#> [169] 0.812910823 0.000000000 0.407438340 0.710355937 0.577676416 0.000000000
#> [175] 0.936485829 0.484909262 0.000000000 0.000000000 0.928419678 0.622583868
#> [181] 0.288505592 0.000000000 0.586773524 0.000000000 0.166456957 0.000000000
#> [187] 0.213576414 0.000000000 0.000000000
#>
#> $Time
#> 1 2 3 5 6 7 8 9 10 11 12 13 14
#> 24.00 24.00 24.00 16.43 15.64 24.00 18.43 24.00 10.53 24.00 24.00 14.34 12.89
#> 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 22.68 8.71 24.00 15.21 24.00 24.00 24.00 24.00 16.92 23.89 6.32 15.77 24.00
#> 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 24.00 15.45 17.43 24.00 20.90 24.00 24.00 24.00 21.19 12.52 24.00 15.59 18.00
#> 41 42 43 44 45 46 47 48 49 51 52 53 54
#> 18.02 12.43 12.10 24.00 17.42 24.00 24.00 24.00 12.19 18.23 10.42 24.00 24.00
#> 55 56 57 58 60 61 62 63 64 65 66 67 68
#> 19.34 12.21 14.46 19.34 13.15 10.12 24.00 22.77 24.00 24.00 22.13 24.00 20.62
#> 69 70 71 72 74 75 76 77 78 79 80 81 82
#> 23.23 7.38 24.00 24.00 24.00 24.00 19.22 7.27 23.88 16.23 24.00 14.06 24.00
#> 83 84 85 86 87 88 90 91 92 93 94 95 96
#> 24.00 24.00 16.44 23.81 24.00 18.37 20.94 5.33 22.92 10.33 24.00 24.00 14.54
#> 97 98 99 100 101 102 103 104 105 106 107 108 109
#> 19.14 24.00 21.19 16.07 9.97 24.00 24.00 24.00 19.75 16.67 11.18 18.29 24.00
#> 110 111 112 113 116 117 118 119 120 121 122 123 125
#> 17.56 17.45 24.00 22.86 24.00 17.46 24.00 24.00 24.00 24.00 24.00 13.00 15.65
#> 126 127 128 129 130 131 132 133 134 135 136 137 138
#> 24.00 3.53 20.35 23.41 16.47 24.00 24.00 14.65 17.81 24.00 21.83 24.00 24.00
#> 139 140 141 142 143 144 145 146 147 148 149 150 151
#> 21.49 12.68 24.00 24.00 24.00 24.00 10.07 24.00 24.00 24.00 8.37 20.33 24.00
#> 152 153 154 155 156 157 158 159 160 161 162 163 164
#> 24.00 21.33 12.63 13.08 24.00 15.10 20.14 10.55 24.00 24.00 24.00 24.00 23.60
#> 165 166 167 168 169 170 171 172 173 174 175 176 177
#> 24.00 19.98 15.55 23.72 22.41 19.54 16.57 24.00 24.00 24.00 21.91 24.00 12.53
#> 178 179 180 181 182 183 184 185 186 187 188 190 191
#> 24.00 18.63 14.82 16.46 24.00 9.24 17.77 24.00 24.00 9.92 16.16 20.81 24.00
#> 192 193 194 196 197 198 200
#> 16.44 24.00 22.40 24.00 21.60 24.00 24.00
#>
#> $bootstrap_fit
#> $bootstrap_fit[[1]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004011182 0.531727504 0.200639269
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.13396974 -0.00404174 0.03055984
#> grade_iii, Cure model
#> 0.57098686
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 106 16.67 1 49 1 0
#> 117 17.46 1 26 0 1
#> 199 19.81 1 NA 0 1
#> 124 9.73 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 40 18.00 1 28 1 0
#> 16 8.71 1 71 0 1
#> 169 22.41 1 46 0 0
#> 124.1 9.73 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 140 12.68 1 59 1 0
#> 150 20.33 1 48 0 0
#> 70 7.38 1 30 1 0
#> 5 16.43 1 51 0 1
#> 23 16.92 1 61 0 0
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 128 20.35 1 35 0 1
#> 5.1 16.43 1 51 0 1
#> 43 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 124.2 9.73 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 39 15.59 1 37 0 1
#> 127 3.53 1 62 0 1
#> 187 9.92 1 39 1 0
#> 164 23.60 1 76 0 1
#> 166 19.98 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 183 9.24 1 67 1 0
#> 117.1 17.46 1 26 0 1
#> 169.1 22.41 1 46 0 0
#> 169.2 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 101.1 9.97 1 10 0 1
#> 79 16.23 1 54 1 0
#> 10 10.53 1 34 0 0
#> 107 11.18 1 54 1 0
#> 42 12.43 1 49 0 1
#> 78 23.88 1 43 0 0
#> 92 22.92 1 47 0 1
#> 43.1 12.10 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 57 14.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 175 21.91 1 43 0 0
#> 56 12.21 1 60 0 0
#> 76 19.22 1 54 0 1
#> 124.3 9.73 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 175.1 21.91 1 43 0 0
#> 194.1 22.40 1 38 0 1
#> 105 19.75 1 60 0 0
#> 96 14.54 1 33 0 1
#> 133 14.65 1 57 0 0
#> 66 22.13 1 53 0 0
#> 128.1 20.35 1 35 0 1
#> 154 12.63 1 20 1 0
#> 123.1 13.00 1 44 1 0
#> 100 16.07 1 60 0 0
#> 36 21.19 1 48 0 1
#> 13 14.34 1 54 0 1
#> 158 20.14 1 74 1 0
#> 63 22.77 1 31 1 0
#> 92.1 22.92 1 47 0 1
#> 108 18.29 1 39 0 1
#> 45 17.42 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 194.2 22.40 1 38 0 1
#> 177 12.53 1 75 0 0
#> 129 23.41 1 53 1 0
#> 175.2 21.91 1 43 0 0
#> 154.1 12.63 1 20 1 0
#> 43.2 12.10 1 61 0 1
#> 49.1 12.19 1 48 1 0
#> 150.1 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 60 13.15 1 38 1 0
#> 155 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 6 15.64 1 39 0 0
#> 157.1 15.10 1 47 0 0
#> 56.1 12.21 1 60 0 0
#> 13.1 14.34 1 54 0 1
#> 93 10.33 1 52 0 1
#> 77 7.27 1 67 0 1
#> 180 14.82 1 37 0 0
#> 100.1 16.07 1 60 0 0
#> 66.1 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 26 15.77 1 49 0 1
#> 43.3 12.10 1 61 0 1
#> 124.4 9.73 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 180.1 14.82 1 37 0 0
#> 70.1 7.38 1 30 1 0
#> 134 17.81 1 47 1 0
#> 86 23.81 1 58 0 1
#> 63.1 22.77 1 31 1 0
#> 158.1 20.14 1 74 1 0
#> 107.1 11.18 1 54 1 0
#> 170 19.54 1 43 0 1
#> 159.1 10.55 1 50 0 1
#> 41 18.02 1 40 1 0
#> 43.4 12.10 1 61 0 1
#> 194.3 22.40 1 38 0 1
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 3 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 109 24.00 0 48 0 0
#> 27 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 34.1 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 161.1 24.00 0 45 0 0
#> 137 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 27.1 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 146 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 146.1 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 34.2 24.00 0 36 0 0
#> 71 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 152.1 24.00 0 36 0 1
#> 72.1 24.00 0 40 0 1
#> 142.1 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 146.2 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 138 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 147 24.00 0 76 1 0
#> 62.1 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 62.2 24.00 0 71 0 0
#> 142.2 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 17 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 19 24.00 0 57 0 1
#> 74.1 24.00 0 43 0 1
#> 191.1 24.00 0 60 0 1
#> 152.2 24.00 0 36 0 1
#> 3.1 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 131 24.00 0 66 0 0
#> 121.2 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 182.1 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 165.1 24.00 0 47 0 0
#> 173.1 24.00 0 19 0 1
#> 142.3 24.00 0 53 0 0
#> 17.1 24.00 0 38 0 1
#> 27.2 24.00 0 63 1 0
#> 62.3 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 103.1 24.00 0 56 1 0
#> 198.1 24.00 0 66 0 1
#> 31.1 24.00 0 36 0 1
#> 12.1 24.00 0 63 0 0
#> 132 24.00 0 55 0 0
#> 103.2 24.00 0 56 1 0
#> 131.1 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 20.1 24.00 0 46 1 0
#> 198.2 24.00 0 66 0 1
#> 196.2 24.00 0 19 0 0
#> 11 24.00 0 42 0 1
#> 172 24.00 0 41 0 0
#> 165.2 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 137.1 24.00 0 45 1 0
#> 147.1 24.00 0 76 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.134 NA NA NA
#> 2 age, Cure model -0.00404 NA NA NA
#> 3 grade_ii, Cure model 0.0306 NA NA NA
#> 4 grade_iii, Cure model 0.571 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00401 NA NA NA
#> 2 grade_ii, Survival model 0.532 NA NA NA
#> 3 grade_iii, Survival model 0.201 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.133970 -0.004042 0.030560 0.570987
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262.4
#> Residual Deviance: 258.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.13396974 -0.00404174 0.03055984 0.57098686
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004011182 0.531727504 0.200639269
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90982598 0.60315576 0.56867069 0.27306045 0.54197432 0.96852678
#> [7] 0.23619225 0.77017327 0.78506286 0.42664071 0.97490440 0.61997891
#> [13] 0.59456131 0.21008580 0.68453481 0.40603136 0.61997891 0.86320694
#> [19] 0.37361098 0.21008580 0.67656675 0.99374486 0.95566611 0.09150467
#> [25] 0.46630755 0.51408317 0.96212280 0.56867069 0.23619225 0.23619225
#> [31] 0.94270998 0.94270998 0.63636295 0.92300055 0.89655657 0.82828003
#> [37] 0.02734658 0.15228391 0.86320694 0.39536984 0.93618501 0.73173348
#> [43] 0.50464907 0.34058535 0.83536376 0.49519076 0.55987751 0.34058535
#> [49] 0.27306045 0.47599946 0.72389040 0.71601360 0.31777469 0.40603136
#> [55] 0.79963294 0.77017327 0.64449113 0.38456452 0.73953775 0.44704106
#> [61] 0.18327741 0.15228391 0.52348150 0.58593229 0.84940663 0.27306045
#> [67] 0.81398235 0.11492333 0.34058535 0.79963294 0.86320694 0.84940663
#> [73] 0.42664071 0.61162096 0.75489700 0.76253934 0.13405744 0.66855930
#> [79] 0.68453481 0.83536376 0.73953775 0.92960460 0.98746730 0.70030250
#> [85] 0.64449113 0.31777469 0.82116663 0.66053557 0.86320694 0.78506286
#> [91] 0.70030250 0.97490440 0.55100262 0.06344453 0.18327741 0.44704106
#> [97] 0.89655657 0.48563798 0.90982598 0.53280798 0.86320694 0.27306045
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 159 106 117 194 40 16 169 123 140 150 70 5 23
#> 10.55 16.67 17.46 22.40 18.00 8.71 22.41 13.00 12.68 20.33 7.38 16.43 16.92
#> 15 157 128 5.1 43 139 15.1 39 127 187 164 166 88
#> 22.68 15.10 20.35 16.43 12.10 21.49 22.68 15.59 3.53 9.92 23.60 19.98 18.37
#> 183 117.1 169.1 169.2 101 101.1 79 10 107 42 78 92 43.1
#> 9.24 17.46 22.41 22.41 9.97 9.97 16.23 10.53 11.18 12.43 23.88 22.92 12.10
#> 90 145 57 8 175 56 76 110 175.1 194.1 105 96 133
#> 20.94 10.07 14.46 18.43 21.91 12.21 19.22 17.56 21.91 22.40 19.75 14.54 14.65
#> 66 128.1 154 123.1 100 36 13 158 63 92.1 108 45 49
#> 22.13 20.35 12.63 13.00 16.07 21.19 14.34 20.14 22.77 22.92 18.29 17.42 12.19
#> 194.2 177 129 175.2 154.1 43.2 49.1 150.1 192 60 155 69 6
#> 22.40 12.53 23.41 21.91 12.63 12.10 12.19 20.33 16.44 13.15 13.08 23.23 15.64
#> 157.1 56.1 13.1 93 77 180 100.1 66.1 37 26 43.3 140.1 180.1
#> 15.10 12.21 14.34 10.33 7.27 14.82 16.07 22.13 12.52 15.77 12.10 12.68 14.82
#> 70.1 134 86 63.1 158.1 107.1 170 159.1 41 43.4 194.3 196 196.1
#> 7.38 17.81 23.81 22.77 20.14 11.18 19.54 10.55 18.02 12.10 22.40 24.00 24.00
#> 34 3 62 165 161 109 27 120 182 84 34.1 156 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 137 74 12 27.1 72 146 142 146.1 53 34.2 71 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 72.1 142.1 98 146.2 121.1 173 138 160 122 191 147 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 62.2 142.2 82 17 103 19 74.1 191.1 152.2 3.1 1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.2 148 182.1 47 143 193 38 31 22 198 165.1 173.1 142.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 27.2 62.3 135 103.1 198.1 31.1 12.1 132 103.2 131.1 20 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.2 196.2 11 172 165.2 174 137.1 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[2]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01707941 0.58948024 0.82135278
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.469397938 0.006511403 0.448186298
#> grade_iii, Cure model
#> 0.690722876
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 197 21.60 1 69 1 0
#> 42 12.43 1 49 0 1
#> 18 15.21 1 49 1 0
#> 8 18.43 1 32 0 0
#> 68 20.62 1 44 0 0
#> 23 16.92 1 61 0 0
#> 15 22.68 1 48 0 0
#> 57 14.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 93 10.33 1 52 0 1
#> 129 23.41 1 53 1 0
#> 105 19.75 1 60 0 0
#> 125 15.65 1 67 1 0
#> 5 16.43 1 51 0 1
#> 24 23.89 1 38 0 0
#> 23.1 16.92 1 61 0 0
#> 97 19.14 1 65 0 1
#> 197.1 21.60 1 69 1 0
#> 4 17.64 1 NA 0 1
#> 39 15.59 1 37 0 1
#> 124 9.73 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 8.1 18.43 1 32 0 0
#> 56 12.21 1 60 0 0
#> 29 15.45 1 68 1 0
#> 187 9.92 1 39 1 0
#> 60 13.15 1 38 1 0
#> 96 14.54 1 33 0 1
#> 114 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 101 9.97 1 10 0 1
#> 78 23.88 1 43 0 0
#> 63 22.77 1 31 1 0
#> 110 17.56 1 65 0 1
#> 79 16.23 1 54 1 0
#> 93.1 10.33 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 105.1 19.75 1 60 0 0
#> 105.2 19.75 1 60 0 0
#> 32 20.90 1 37 1 0
#> 188 16.16 1 46 0 1
#> 61 10.12 1 36 0 1
#> 30 17.43 1 78 0 0
#> 133 14.65 1 57 0 0
#> 97.1 19.14 1 65 0 1
#> 29.1 15.45 1 68 1 0
#> 97.2 19.14 1 65 0 1
#> 81 14.06 1 34 0 0
#> 184 17.77 1 38 0 0
#> 69 23.23 1 25 0 1
#> 89 11.44 1 NA 0 0
#> 127 3.53 1 62 0 1
#> 130 16.47 1 53 0 1
#> 76 19.22 1 54 0 1
#> 166 19.98 1 48 0 0
#> 140 12.68 1 59 1 0
#> 168 23.72 1 70 0 0
#> 14 12.89 1 21 0 0
#> 55 19.34 1 69 0 1
#> 101.1 9.97 1 10 0 1
#> 113 22.86 1 34 0 0
#> 107 11.18 1 54 1 0
#> 149 8.37 1 33 1 0
#> 153 21.33 1 55 1 0
#> 18.1 15.21 1 49 1 0
#> 154 12.63 1 20 1 0
#> 111.1 17.45 1 47 0 1
#> 43 12.10 1 61 0 1
#> 195 11.76 1 NA 1 0
#> 197.2 21.60 1 69 1 0
#> 42.1 12.43 1 49 0 1
#> 88 18.37 1 47 0 0
#> 55.1 19.34 1 69 0 1
#> 134.1 17.81 1 47 1 0
#> 39.1 15.59 1 37 0 1
#> 58 19.34 1 39 0 0
#> 101.2 9.97 1 10 0 1
#> 24.1 23.89 1 38 0 0
#> 154.1 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 197.3 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 136 21.83 1 43 0 1
#> 130.1 16.47 1 53 0 1
#> 190 20.81 1 42 1 0
#> 14.1 12.89 1 21 0 0
#> 60.1 13.15 1 38 1 0
#> 168.1 23.72 1 70 0 0
#> 92 22.92 1 47 0 1
#> 197.4 21.60 1 69 1 0
#> 153.1 21.33 1 55 1 0
#> 43.1 12.10 1 61 0 1
#> 100 16.07 1 60 0 0
#> 60.2 13.15 1 38 1 0
#> 130.2 16.47 1 53 0 1
#> 123 13.00 1 44 1 0
#> 60.3 13.15 1 38 1 0
#> 68.1 20.62 1 44 0 0
#> 155 13.08 1 26 0 0
#> 6 15.64 1 39 0 0
#> 129.1 23.41 1 53 1 0
#> 52 10.42 1 52 0 1
#> 78.1 23.88 1 43 0 0
#> 183.1 9.24 1 67 1 0
#> 190.1 20.81 1 42 1 0
#> 18.2 15.21 1 49 1 0
#> 79.1 16.23 1 54 1 0
#> 10 10.53 1 34 0 0
#> 184.1 17.77 1 38 0 0
#> 197.5 21.60 1 69 1 0
#> 112 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 80 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 178 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 185 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 7 24.00 0 37 1 0
#> 38 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 65 24.00 0 57 1 0
#> 193 24.00 0 45 0 1
#> 27 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 84 24.00 0 39 0 1
#> 31 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 44 24.00 0 56 0 0
#> 47 24.00 0 38 0 1
#> 109 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 182.1 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 64 24.00 0 43 0 0
#> 193.1 24.00 0 45 0 1
#> 148 24.00 0 61 1 0
#> 138 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 21 24.00 0 47 0 0
#> 112.1 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 53 24.00 0 32 0 1
#> 84.1 24.00 0 39 0 1
#> 54 24.00 0 53 1 0
#> 176.1 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 21.1 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 115 24.00 0 NA 1 0
#> 141 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 132.1 24.00 0 55 0 0
#> 193.2 24.00 0 45 0 1
#> 121.1 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 138.1 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 148.1 24.00 0 61 1 0
#> 17 24.00 0 38 0 1
#> 71.1 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 112.2 24.00 0 61 0 0
#> 82 24.00 0 34 0 0
#> 28 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 163 24.00 0 66 0 0
#> 71.2 24.00 0 51 0 0
#> 7.1 24.00 0 37 1 0
#> 9 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 12 24.00 0 63 0 0
#> 82.1 24.00 0 34 0 0
#> 112.3 24.00 0 61 0 0
#> 191 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 109.1 24.00 0 48 0 0
#> 178.1 24.00 0 52 1 0
#> 126.2 24.00 0 48 0 0
#> 20.1 24.00 0 46 1 0
#> 137 24.00 0 45 1 0
#> 44.1 24.00 0 56 0 0
#> 198 24.00 0 66 0 1
#> 2.1 24.00 0 9 0 0
#> 64.1 24.00 0 43 0 0
#> 198.1 24.00 0 66 0 1
#> 33 24.00 0 53 0 0
#> 9.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.469 NA NA NA
#> 2 age, Cure model 0.00651 NA NA NA
#> 3 grade_ii, Cure model 0.448 NA NA NA
#> 4 grade_iii, Cure model 0.691 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0171 NA NA NA
#> 2 grade_ii, Survival model 0.589 NA NA NA
#> 3 grade_iii, Survival model 0.821 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.469398 0.006511 0.448186 0.690723
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 260.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.469397938 0.006511403 0.448186298 0.690722876
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01707941 0.58948024 0.82135278
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0609645567 0.7637263745 0.5461632852 0.2546734214 0.1363380044
#> [6] 0.3657394884 0.0496773205 0.6056421577 0.0138174913 0.8639725432
#> [11] 0.0188304515 0.1590075423 0.4764261813 0.4201423520 0.0003493298
#> [16] 0.3657394884 0.2184371185 0.0609645567 0.4997637906 0.2837658622
#> [21] 0.2546734214 0.7883204374 0.5227392787 0.9383118879 0.6298782023
#> [26] 0.5935634622 0.3344732228 0.9020538046 0.0023677047 0.0443483780
#> [31] 0.3240039027 0.4312971330 0.8639725432 0.2452173499 0.1590075423
#> [36] 0.1590075423 0.1151802226 0.4536413398 0.8893268781 0.3550607287
#> [41] 0.5814120811 0.2184371185 0.5227392787 0.2184371185 0.6177078200
#> [46] 0.3035665251 0.0288466843 0.9875801988 0.3875994388 0.2094097138
#> [51] 0.1511762367 0.7266317459 0.0064210478 0.7019654628 0.1835805822
#> [56] 0.9020538046 0.0389803716 0.8258402401 0.9751933396 0.1014017620
#> [61] 0.5461632852 0.7391445840 0.3344732228 0.8008411165 0.0609645567
#> [66] 0.7637263745 0.2738224528 0.1835805822 0.2837658622 0.4997637906
#> [71] 0.1835805822 0.9020538046 0.0003493298 0.7391445840 0.0945474893
#> [76] 0.0609645567 0.9505688213 0.0553467997 0.3875994388 0.1223072326
#> [81] 0.7019654628 0.6298782023 0.0064210478 0.0339199176 0.0609645567
#> [86] 0.1014017620 0.8008411165 0.4649442807 0.6298782023 0.3875994388
#> [91] 0.6896536292 0.6298782023 0.1363380044 0.6773745875 0.4880271466
#> [96] 0.0188304515 0.8512253494 0.0023677047 0.9505688213 0.1223072326
#> [101] 0.5461632852 0.4312971330 0.8384904777 0.3035665251 0.0609645567
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000
#>
#> $Time
#> 197 42 18 8 68 23 15 57 164 93 129 105 125
#> 21.60 12.43 15.21 18.43 20.62 16.92 22.68 14.46 23.60 10.33 23.41 19.75 15.65
#> 5 24 23.1 97 197.1 39 134 8.1 56 29 187 60 96
#> 16.43 23.89 16.92 19.14 21.60 15.59 17.81 18.43 12.21 15.45 9.92 13.15 14.54
#> 111 101 78 63 110 79 93.1 179 105.1 105.2 32 188 61
#> 17.45 9.97 23.88 22.77 17.56 16.23 10.33 18.63 19.75 19.75 20.90 16.16 10.12
#> 30 133 97.1 29.1 97.2 81 184 69 127 130 76 166 140
#> 17.43 14.65 19.14 15.45 19.14 14.06 17.77 23.23 3.53 16.47 19.22 19.98 12.68
#> 168 14 55 101.1 113 107 149 153 18.1 154 111.1 43 197.2
#> 23.72 12.89 19.34 9.97 22.86 11.18 8.37 21.33 15.21 12.63 17.45 12.10 21.60
#> 42.1 88 55.1 134.1 39.1 58 101.2 24.1 154.1 139 197.3 183 136
#> 12.43 18.37 19.34 17.81 15.59 19.34 9.97 23.89 12.63 21.49 21.60 9.24 21.83
#> 130.1 190 14.1 60.1 168.1 92 197.4 153.1 43.1 100 60.2 130.2 123
#> 16.47 20.81 12.89 13.15 23.72 22.92 21.60 21.33 12.10 16.07 13.15 16.47 13.00
#> 60.3 68.1 155 6 129.1 52 78.1 183.1 190.1 18.2 79.1 10 184.1
#> 13.15 20.62 13.08 15.64 23.41 10.42 23.88 9.24 20.81 15.21 16.23 10.53 17.77
#> 197.5 112 119 80 118 98 178 160 176 143 147 185 120
#> 21.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 7 38 182 65 193 27 2 84 31 34 44 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 152 46 182.1 121 144 64 193.1 148 138 27.1 21 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 53 84.1 54 176.1 71 131 21.1 72 141 172 132.1 193.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 20 138.1 126 148.1 17 71.1 67 112.2 82 28 94 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 7.1 9 126.1 103 12 82.1 112.3 191 161 109.1 178.1 126.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 137 44.1 198 2.1 64.1 198.1 33 9.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[3]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01414053 0.63570025 0.65302588
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.340649475 -0.006238602 -0.137803131
#> grade_iii, Cure model
#> 0.591989145
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 130 16.47 1 53 0 1
#> 101 9.97 1 10 0 1
#> 187 9.92 1 39 1 0
#> 86 23.81 1 58 0 1
#> 45 17.42 1 54 0 1
#> 150 20.33 1 48 0 0
#> 96 14.54 1 33 0 1
#> 101.1 9.97 1 10 0 1
#> 26 15.77 1 49 0 1
#> 164 23.60 1 76 0 1
#> 45.1 17.42 1 54 0 1
#> 125 15.65 1 67 1 0
#> 55 19.34 1 69 0 1
#> 155 13.08 1 26 0 0
#> 63 22.77 1 31 1 0
#> 107 11.18 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 25 6.32 1 34 1 0
#> 70 7.38 1 30 1 0
#> 187.1 9.92 1 39 1 0
#> 60 13.15 1 38 1 0
#> 180 14.82 1 37 0 0
#> 88 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 189 10.51 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 49 12.19 1 48 1 0
#> 127 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 29 15.45 1 68 1 0
#> 99 21.19 1 38 0 1
#> 192 16.44 1 31 1 0
#> 5 16.43 1 51 0 1
#> 101.2 9.97 1 10 0 1
#> 140 12.68 1 59 1 0
#> 111 17.45 1 47 0 1
#> 169 22.41 1 46 0 0
#> 5.1 16.43 1 51 0 1
#> 77 7.27 1 67 0 1
#> 18 15.21 1 49 1 0
#> 90 20.94 1 50 0 1
#> 45.2 17.42 1 54 0 1
#> 36 21.19 1 48 0 1
#> 167 15.55 1 56 1 0
#> 168 23.72 1 70 0 0
#> 78 23.88 1 43 0 0
#> 79 16.23 1 54 1 0
#> 155.1 13.08 1 26 0 0
#> 153 21.33 1 55 1 0
#> 150.1 20.33 1 48 0 0
#> 181 16.46 1 45 0 1
#> 45.3 17.42 1 54 0 1
#> 16 8.71 1 71 0 1
#> 15 22.68 1 48 0 0
#> 52 10.42 1 52 0 1
#> 76 19.22 1 54 0 1
#> 61 10.12 1 36 0 1
#> 76.1 19.22 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 111.1 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 60.1 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 184 17.77 1 38 0 0
#> 124.1 9.73 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 18.1 15.21 1 49 1 0
#> 24 23.89 1 38 0 0
#> 43 12.10 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 61.1 10.12 1 36 0 1
#> 175 21.91 1 43 0 0
#> 101.3 9.97 1 10 0 1
#> 6.1 15.64 1 39 0 0
#> 51.1 18.23 1 83 0 1
#> 136 21.83 1 43 0 1
#> 105 19.75 1 60 0 0
#> 179 18.63 1 42 0 0
#> 15.1 22.68 1 48 0 0
#> 56 12.21 1 60 0 0
#> 154 12.63 1 20 1 0
#> 149 8.37 1 33 1 0
#> 6.2 15.64 1 39 0 0
#> 63.2 22.77 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 99.1 21.19 1 38 0 1
#> 187.2 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 90.1 20.94 1 50 0 1
#> 197 21.60 1 69 1 0
#> 76.2 19.22 1 54 0 1
#> 81 14.06 1 34 0 0
#> 41 18.02 1 40 1 0
#> 88.1 18.37 1 47 0 0
#> 42.1 12.43 1 49 0 1
#> 149.1 8.37 1 33 1 0
#> 197.1 21.60 1 69 1 0
#> 85 16.44 1 36 0 0
#> 197.2 21.60 1 69 1 0
#> 133 14.65 1 57 0 0
#> 60.2 13.15 1 38 1 0
#> 51.2 18.23 1 83 0 1
#> 66 22.13 1 53 0 0
#> 166 19.98 1 48 0 0
#> 139.1 21.49 1 63 1 0
#> 117 17.46 1 26 0 1
#> 39 15.59 1 37 0 1
#> 142 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 163 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 28 24.00 0 67 1 0
#> 186 24.00 0 45 1 0
#> 3 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 47 24.00 0 38 0 1
#> 163.1 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 38 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 74 24.00 0 43 0 1
#> 156 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 200 24.00 0 64 0 0
#> 174 24.00 0 49 1 0
#> 102.1 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 103 24.00 0 56 1 0
#> 151 24.00 0 42 0 0
#> 28.1 24.00 0 67 1 0
#> 54.1 24.00 0 53 1 0
#> 48 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 94 24.00 0 51 0 1
#> 142.1 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 38.1 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 122.1 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 151.1 24.00 0 42 0 0
#> 19.1 24.00 0 57 0 1
#> 46.1 24.00 0 71 0 0
#> 28.2 24.00 0 67 1 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 200.1 24.00 0 64 0 0
#> 1.1 24.00 0 23 1 0
#> 80 24.00 0 41 0 0
#> 131.1 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 120.1 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 28.3 24.00 0 67 1 0
#> 74.1 24.00 0 43 0 1
#> 144 24.00 0 28 0 1
#> 47.2 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 83 24.00 0 6 0 0
#> 80.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 48.1 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 138.1 24.00 0 44 1 0
#> 54.2 24.00 0 53 1 0
#> 11 24.00 0 42 0 1
#> 1.2 24.00 0 23 1 0
#> 193.1 24.00 0 45 0 1
#> 120.2 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 72.1 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 147.1 24.00 0 76 1 0
#> 21.1 24.00 0 47 0 0
#> 132.1 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 174.1 24.00 0 49 1 0
#> 191 24.00 0 60 0 1
#> 74.2 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.341 NA NA NA
#> 2 age, Cure model -0.00624 NA NA NA
#> 3 grade_ii, Cure model -0.138 NA NA NA
#> 4 grade_iii, Cure model 0.592 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0141 NA NA NA
#> 2 grade_ii, Survival model 0.636 NA NA NA
#> 3 grade_iii, Survival model 0.653 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.340649 -0.006239 -0.137803 0.591989
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 260.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.340649475 -0.006238602 -0.137803131 0.591989145
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01414053 0.63570025 0.65302588
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4159156412 0.8388000081 0.8813984114 0.0063546290 0.3663435730
#> [6] 0.1806571465 0.6168548336 0.8388000081 0.4882472300 0.0161470572
#> [11] 0.3663435730 0.4987041818 0.2148410686 0.6935602234 0.0296954212
#> [16] 0.7938725262 0.4055793068 0.9783467644 0.9567080004 0.8813984114
#> [21] 0.6609118060 0.5948540645 0.2592812010 0.1725256479 0.0225290118
#> [26] 0.7713708957 0.9891615060 0.5092201923 0.5624805150 0.1332596499
#> [31] 0.4366314402 0.4571846393 0.8388000081 0.7157159330 0.3366656235
#> [36] 0.0570892573 0.4571846393 0.9675119550 0.5733250976 0.1565199664
#> [41] 0.3663435730 0.1332596499 0.5516937709 0.0105440476 0.0026201217
#> [46] 0.4777990306 0.6935602234 0.1248956208 0.1806571465 0.4262756538
#> [51] 0.3663435730 0.9242845135 0.0448513103 0.8051578597 0.2238337745
#> [56] 0.8164557036 0.2238337745 0.0296954212 0.3366656235 0.7380362348
#> [61] 0.6609118060 0.6278700418 0.6278700418 0.3167182633 0.3562333751
#> [66] 0.5733250976 0.0004732043 0.7826064212 0.2780249270 0.8164557036
#> [71] 0.0712229123 0.8388000081 0.5092201923 0.2780249270 0.0788509202
#> [76] 0.2059510262 0.2500634117 0.0448513103 0.7601422637 0.7269123344
#> [81] 0.9351651322 0.5092201923 0.0296954212 0.9134416754 0.1332596499
#> [86] 0.8813984114 0.1088652359 0.1565199664 0.0864457226 0.2238337745
#> [91] 0.6497870657 0.3068245116 0.2592812010 0.7380362348 0.9351651322
#> [96] 0.0864457226 0.4366314402 0.0864457226 0.6057991820 0.6609118060
#> [101] 0.2780249270 0.0639501536 0.1972751898 0.1088652359 0.3267421985
#> [106] 0.5409374401 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 130 101 187 86 45 150 96 101.1 26 164 45.1 125 55
#> 16.47 9.97 9.92 23.81 17.42 20.33 14.54 9.97 15.77 23.60 17.42 15.65 19.34
#> 155 63 107 23 25 70 187.1 60 180 88 128 113 49
#> 13.08 22.77 11.18 16.92 6.32 7.38 9.92 13.15 14.82 18.37 20.35 22.86 12.19
#> 127 6 29 99 192 5 101.2 140 111 169 5.1 77 18
#> 3.53 15.64 15.45 21.19 16.44 16.43 9.97 12.68 17.45 22.41 16.43 7.27 15.21
#> 90 45.2 36 167 168 78 79 155.1 153 150.1 181 45.3 16
#> 20.94 17.42 21.19 15.55 23.72 23.88 16.23 13.08 21.33 20.33 16.46 17.42 8.71
#> 15 52 76 61 76.1 63.1 111.1 42 60.1 13 13.1 184 30
#> 22.68 10.42 19.22 10.12 19.22 22.77 17.45 12.43 13.15 14.34 14.34 17.77 17.43
#> 18.1 24 43 51 61.1 175 101.3 6.1 51.1 136 105 179 15.1
#> 15.21 23.89 12.10 18.23 10.12 21.91 9.97 15.64 18.23 21.83 19.75 18.63 22.68
#> 56 154 149 6.2 63.2 183 99.1 187.2 139 90.1 197 76.2 81
#> 12.21 12.63 8.37 15.64 22.77 9.24 21.19 9.92 21.49 20.94 21.60 19.22 14.06
#> 41 88.1 42.1 149.1 197.1 85 197.2 133 60.2 51.2 66 166 139.1
#> 18.02 18.37 12.43 8.37 21.60 16.44 21.60 14.65 13.15 18.23 22.13 19.98 21.49
#> 117 39 142 131 19 163 28 186 3 102 47 163.1 120
#> 17.46 15.59 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 7 74 156 31 122 21 72 200 174 102.1 46 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 151 28.1 54.1 48 1 94 142.1 95 119 38.1 186.1 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 141 118 132 151.1 19.1 46.1 28.2 193 116 98 200.1 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 131.1 147 120.1 53 28.3 74.1 144 47.2 62 83 80.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 178 109 9 182 138 118.1 138.1 54.2 11 1.2 193.1 120.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 172 72.1 27 147.1 21.1 132.1 148 174.1 191 74.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[4]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00916749 0.67781906 0.48504691
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.0227423391 -0.0004727542 0.1098464406
#> grade_iii, Cure model
#> 0.5119416273
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 77 7.27 1 67 0 1
#> 96 14.54 1 33 0 1
#> 88 18.37 1 47 0 0
#> 106 16.67 1 49 1 0
#> 60 13.15 1 38 1 0
#> 170 19.54 1 43 0 1
#> 69 23.23 1 25 0 1
#> 169 22.41 1 46 0 0
#> 89 11.44 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 16 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 170.1 19.54 1 43 0 1
#> 197 21.60 1 69 1 0
#> 24 23.89 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 155 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 36 21.19 1 48 0 1
#> 30 17.43 1 78 0 0
#> 6 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 78 23.88 1 43 0 0
#> 66 22.13 1 53 0 0
#> 42 12.43 1 49 0 1
#> 90 20.94 1 50 0 1
#> 169.1 22.41 1 46 0 0
#> 15.1 22.68 1 48 0 0
#> 51 18.23 1 83 0 1
#> 43 12.10 1 61 0 1
#> 169.2 22.41 1 46 0 0
#> 63 22.77 1 31 1 0
#> 16.1 8.71 1 71 0 1
#> 123 13.00 1 44 1 0
#> 69.1 23.23 1 25 0 1
#> 66.1 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 10 10.53 1 34 0 0
#> 139 21.49 1 63 1 0
#> 195 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 51.1 18.23 1 83 0 1
#> 59 10.16 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 16.2 8.71 1 71 0 1
#> 30.1 17.43 1 78 0 0
#> 168 23.72 1 70 0 0
#> 8.1 18.43 1 32 0 0
#> 134 17.81 1 47 1 0
#> 106.1 16.67 1 49 1 0
#> 153 21.33 1 55 1 0
#> 145 10.07 1 65 1 0
#> 153.1 21.33 1 55 1 0
#> 123.1 13.00 1 44 1 0
#> 125 15.65 1 67 1 0
#> 69.2 23.23 1 25 0 1
#> 68 20.62 1 44 0 0
#> 25 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 18 15.21 1 49 1 0
#> 51.2 18.23 1 83 0 1
#> 86 23.81 1 58 0 1
#> 108 18.29 1 39 0 1
#> 179.1 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 159 10.55 1 50 0 1
#> 110 17.56 1 65 0 1
#> 15.2 22.68 1 48 0 0
#> 139.1 21.49 1 63 1 0
#> 134.1 17.81 1 47 1 0
#> 63.1 22.77 1 31 1 0
#> 111 17.45 1 47 0 1
#> 4.1 17.64 1 NA 0 1
#> 88.1 18.37 1 47 0 0
#> 155.1 13.08 1 26 0 0
#> 166 19.98 1 48 0 0
#> 5.1 16.43 1 51 0 1
#> 168.1 23.72 1 70 0 0
#> 195.1 11.76 1 NA 1 0
#> 197.1 21.60 1 69 1 0
#> 91 5.33 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 108.1 18.29 1 39 0 1
#> 199 19.81 1 NA 0 1
#> 195.2 11.76 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 24.1 23.89 1 38 0 0
#> 145.1 10.07 1 65 1 0
#> 49.1 12.19 1 48 1 0
#> 86.1 23.81 1 58 0 1
#> 154.1 12.63 1 20 1 0
#> 69.3 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 123.2 13.00 1 44 1 0
#> 108.2 18.29 1 39 0 1
#> 4.2 17.64 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 13.1 14.34 1 54 0 1
#> 199.1 19.81 1 NA 0 1
#> 106.2 16.67 1 49 1 0
#> 85.1 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 56 12.21 1 60 0 0
#> 105 19.75 1 60 0 0
#> 97.1 19.14 1 65 0 1
#> 129 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 99.1 21.19 1 38 0 1
#> 64 24.00 0 43 0 0
#> 27 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 17 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 17.1 24.00 0 38 0 1
#> 84.1 24.00 0 39 0 1
#> 22.1 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 38 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 17.2 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 126 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 94.1 24.00 0 51 0 1
#> 67 24.00 0 25 0 0
#> 172 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 196 24.00 0 19 0 0
#> 146 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 193 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 160 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 12.1 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 198 24.00 0 66 0 1
#> 73.1 24.00 0 NA 0 1
#> 67.1 24.00 0 25 0 0
#> 95 24.00 0 68 0 1
#> 38.1 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 95.1 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 27.1 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 11 24.00 0 42 0 1
#> 54.1 24.00 0 53 1 0
#> 163 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 182 24.00 0 35 0 0
#> 191 24.00 0 60 0 1
#> 162 24.00 0 51 0 0
#> 62.1 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 112.1 24.00 0 61 0 0
#> 116.1 24.00 0 58 0 1
#> 172.1 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 54.2 24.00 0 53 1 0
#> 115 24.00 0 NA 1 0
#> 163.1 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 148.1 24.00 0 61 1 0
#> 73.2 24.00 0 NA 0 1
#> 173.1 24.00 0 19 0 1
#> 22.2 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 116.2 24.00 0 58 0 1
#> 163.2 24.00 0 66 0 0
#> 116.3 24.00 0 58 0 1
#> 143 24.00 0 51 0 0
#> 22.3 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#> 21 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 160.1 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 115.1 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0227 NA NA NA
#> 2 age, Cure model -0.000473 NA NA NA
#> 3 grade_ii, Cure model 0.110 NA NA NA
#> 4 grade_iii, Cure model 0.512 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00917 NA NA NA
#> 2 grade_ii, Survival model 0.678 NA NA NA
#> 3 grade_iii, Survival model 0.485 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.0227423 -0.0004728 0.1098464 0.5119416
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.5
#> Residual Deviance: 252.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.0227423391 -0.0004727542 0.1098464406 0.5119416273
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00916749 0.67781906 0.48504691
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.98776243 0.86366942 0.70436764 0.79341344 0.87878684 0.63877009
#> [7] 0.33314791 0.45510580 0.58251014 0.97115984 0.90793180 0.63877009
#> [13] 0.52608635 0.08666096 0.67590630 0.88375196 0.86878376 0.65390742
#> [19] 0.58251014 0.78169475 0.85330237 0.41762858 0.17553615 0.49103353
#> [25] 0.92206167 0.60687171 0.45510580 0.41762858 0.73855892 0.94046213
#> [31] 0.45510580 0.39091045 0.97115984 0.89362454 0.33314791 0.49103353
#> [37] 0.93137519 0.95821427 0.54649132 0.69018698 0.73855892 0.66148250
#> [43] 0.97115984 0.78169475 0.27114378 0.69018698 0.75744502 0.79341344
#> [49] 0.56514860 0.96260292 0.56514860 0.89362454 0.84807246 0.33314791
#> [55] 0.61493187 0.99187084 0.83205725 0.85851855 0.73855892 0.22129653
#> [61] 0.71839620 0.67590630 0.81015541 0.95381826 0.76967421 0.41762858
#> [67] 0.54649132 0.75744502 0.39091045 0.77571938 0.70436764 0.88375196
#> [73] 0.62293989 0.83205725 0.27114378 0.52608635 0.99595069 0.94046213
#> [79] 0.98361953 0.71839620 0.81015541 0.51456072 0.08666096 0.96260292
#> [85] 0.93137519 0.22129653 0.90793180 0.33314791 0.82113488 0.89362454
#> [91] 0.71839620 0.94939023 0.86878376 0.79341344 0.82113488 0.84275598
#> [97] 0.92672701 0.63089140 0.66148250 0.31394779 0.91735957 0.58251014
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 77 96 88 106 60 170 69 169 99 16 154 170.1 197
#> 7.27 14.54 18.37 16.67 13.15 19.54 23.23 22.41 21.19 8.71 12.63 19.54 21.60
#> 24 179 155 13 58 36 30 6 15 78 66 42 90
#> 23.89 18.63 13.08 14.34 19.34 21.19 17.43 15.64 22.68 23.88 22.13 12.43 20.94
#> 169.1 15.1 51 43 169.2 63 16.1 123 69.1 66.1 49 10 139
#> 22.41 22.68 18.23 12.10 22.41 22.77 8.71 13.00 23.23 22.13 12.19 10.53 21.49
#> 8 51.1 97 16.2 30.1 168 8.1 134 106.1 153 145 153.1 123.1
#> 18.43 18.23 19.14 8.71 17.43 23.72 18.43 17.81 16.67 21.33 10.07 21.33 13.00
#> 125 69.2 68 25 5 18 51.2 86 108 179.1 181 159 110
#> 15.65 23.23 20.62 6.32 16.43 15.21 18.23 23.81 18.29 18.63 16.46 10.55 17.56
#> 15.2 139.1 134.1 63.1 111 88.1 155.1 166 5.1 168.1 197.1 91 43.1
#> 22.68 21.49 17.81 22.77 17.45 18.37 13.08 19.98 16.43 23.72 21.60 5.33 12.10
#> 70 108.1 181.1 136 24.1 145.1 49.1 86.1 154.1 69.3 85 123.2 108.2
#> 7.38 18.29 16.46 21.83 23.89 10.07 12.19 23.81 12.63 23.23 16.44 13.00 18.29
#> 107 13.1 106.2 85.1 188 56 105 97.1 129 177 99.1 64 27
#> 11.18 14.34 16.67 16.44 16.16 12.21 19.75 19.14 23.41 12.53 21.19 24.00 24.00
#> 12 17 22 84 17.1 84.1 22.1 112 38 28 65 71 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 156 126 126.1 94 173 94.1 67 172 165 196 146 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 34.1 1 193 103 160 71.1 47 156.1 12.1 72 31 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 67.1 95 38.1 198.1 54 95.1 109 27.1 174 11 54.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 182 191 162 62.1 132 112.1 116.1 172.1 20 54.2 163.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 173.1 22.2 131 161 116.2 163.2 116.3 143 22.3 200 21 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 160.1 196.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[5]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001035228 0.602189848 0.395185913
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.304540150 0.006515589 -0.121646511
#> grade_iii, Cure model
#> 0.732650235
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 88 18.37 1 47 0 0
#> 18.1 15.21 1 49 1 0
#> 179 18.63 1 42 0 0
#> 18.2 15.21 1 49 1 0
#> 177 12.53 1 75 0 0
#> 55 19.34 1 69 0 1
#> 76 19.22 1 54 0 1
#> 66 22.13 1 53 0 0
#> 39 15.59 1 37 0 1
#> 70 7.38 1 30 1 0
#> 52 10.42 1 52 0 1
#> 16 8.71 1 71 0 1
#> 66.1 22.13 1 53 0 0
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 105 19.75 1 60 0 0
#> 70.1 7.38 1 30 1 0
#> 55.1 19.34 1 69 0 1
#> 13 14.34 1 54 0 1
#> 184 17.77 1 38 0 0
#> 42 12.43 1 49 0 1
#> 66.2 22.13 1 53 0 0
#> 128 20.35 1 35 0 1
#> 159 10.55 1 50 0 1
#> 180 14.82 1 37 0 0
#> 39.1 15.59 1 37 0 1
#> 145 10.07 1 65 1 0
#> 25 6.32 1 34 1 0
#> 199 19.81 1 NA 0 1
#> 139 21.49 1 63 1 0
#> 66.3 22.13 1 53 0 0
#> 180.1 14.82 1 37 0 0
#> 79 16.23 1 54 1 0
#> 6 15.64 1 39 0 0
#> 60 13.15 1 38 1 0
#> 166 19.98 1 48 0 0
#> 70.2 7.38 1 30 1 0
#> 49 12.19 1 48 1 0
#> 10 10.53 1 34 0 0
#> 108 18.29 1 39 0 1
#> 110 17.56 1 65 0 1
#> 89 11.44 1 NA 0 0
#> 159.1 10.55 1 50 0 1
#> 177.1 12.53 1 75 0 0
#> 15 22.68 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 107 11.18 1 54 1 0
#> 145.1 10.07 1 65 1 0
#> 29 15.45 1 68 1 0
#> 145.2 10.07 1 65 1 0
#> 6.2 15.64 1 39 0 0
#> 26 15.77 1 49 0 1
#> 36 21.19 1 48 0 1
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 159.2 10.55 1 50 0 1
#> 10.1 10.53 1 34 0 0
#> 37 12.52 1 57 1 0
#> 50 10.02 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 139.1 21.49 1 63 1 0
#> 127 3.53 1 62 0 1
#> 29.1 15.45 1 68 1 0
#> 69 23.23 1 25 0 1
#> 68.1 20.62 1 44 0 0
#> 69.1 23.23 1 25 0 1
#> 194.1 22.40 1 38 0 1
#> 188 16.16 1 46 0 1
#> 189 10.51 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 15.1 22.68 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 108.1 18.29 1 39 0 1
#> 18.3 15.21 1 49 1 0
#> 70.3 7.38 1 30 1 0
#> 90 20.94 1 50 0 1
#> 91 5.33 1 61 0 1
#> 139.2 21.49 1 63 1 0
#> 101.1 9.97 1 10 0 1
#> 96.1 14.54 1 33 0 1
#> 78 23.88 1 43 0 0
#> 59.1 10.16 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 69.2 23.23 1 25 0 1
#> 79.1 16.23 1 54 1 0
#> 197 21.60 1 69 1 0
#> 110.1 17.56 1 65 0 1
#> 63 22.77 1 31 1 0
#> 187.1 9.92 1 39 1 0
#> 149 8.37 1 33 1 0
#> 167 15.55 1 56 1 0
#> 88.1 18.37 1 47 0 0
#> 101.2 9.97 1 10 0 1
#> 158 20.14 1 74 1 0
#> 175 21.91 1 43 0 0
#> 136 21.83 1 43 0 1
#> 41 18.02 1 40 1 0
#> 169 22.41 1 46 0 0
#> 108.2 18.29 1 39 0 1
#> 114 13.68 1 NA 0 0
#> 189.1 10.51 1 NA 1 0
#> 179.1 18.63 1 42 0 0
#> 129 23.41 1 53 1 0
#> 70.4 7.38 1 30 1 0
#> 124 9.73 1 NA 1 0
#> 139.3 21.49 1 63 1 0
#> 8 18.43 1 32 0 0
#> 91.1 5.33 1 61 0 1
#> 193 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 135 24.00 0 58 1 0
#> 122 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 98.1 24.00 0 34 1 0
#> 75 24.00 0 21 1 0
#> 47 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 83 24.00 0 6 0 0
#> 34 24.00 0 36 0 0
#> 148 24.00 0 61 1 0
#> 137 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 112 24.00 0 61 0 0
#> 48 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 104.1 24.00 0 50 1 0
#> 104.2 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 176.1 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 147.1 24.00 0 76 1 0
#> 118 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 138 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 144 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 162.1 24.00 0 51 0 0
#> 120.1 24.00 0 68 0 1
#> 98.2 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 75.1 24.00 0 21 1 0
#> 148.1 24.00 0 61 1 0
#> 38.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 53.1 24.00 0 32 0 1
#> 44 24.00 0 56 0 0
#> 115 24.00 0 NA 1 0
#> 21 24.00 0 47 0 0
#> 122.1 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 19 24.00 0 57 0 1
#> 185 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 122.2 24.00 0 66 0 0
#> 162.2 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 186 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 178 24.00 0 52 1 0
#> 7.1 24.00 0 37 1 0
#> 67 24.00 0 25 0 0
#> 94 24.00 0 51 0 1
#> 46 24.00 0 71 0 0
#> 104.3 24.00 0 50 1 0
#> 137.1 24.00 0 45 1 0
#> 142 24.00 0 53 0 0
#> 118.1 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 186.1 24.00 0 45 1 0
#> 83.1 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#> 46.1 24.00 0 71 0 0
#> 48.1 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 135.1 24.00 0 58 1 0
#> 191 24.00 0 60 0 1
#> 132.1 24.00 0 55 0 0
#> 65.1 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 147.2 24.00 0 76 1 0
#> 21.1 24.00 0 47 0 0
#> 11.1 24.00 0 42 0 1
#> 11.2 24.00 0 42 0 1
#> 135.2 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.305 NA NA NA
#> 2 age, Cure model 0.00652 NA NA NA
#> 3 grade_ii, Cure model -0.122 NA NA NA
#> 4 grade_iii, Cure model 0.733 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00104 NA NA NA
#> 2 grade_ii, Survival model 0.602 NA NA NA
#> 3 grade_iii, Survival model 0.395 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.304540 0.006516 -0.121647 0.732650
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 255.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.304540150 0.006515589 -0.121646511 0.732650235
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001035228 0.602189848 0.395185913
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.69884937 0.37293146 0.89591087 0.49974782 0.69884937 0.47137372
#> [7] 0.69884937 0.77464248 0.43346358 0.46183110 0.22260013 0.65815452
#> [13] 0.94285571 0.86838869 0.92953448 0.22260013 0.81164856 0.81164856
#> [19] 0.42352096 0.94285571 0.43346358 0.75958591 0.55479902 0.79695377
#> [25] 0.22260013 0.39337865 0.83324675 0.72915277 0.65815452 0.87542837
#> [31] 0.97461494 0.31091704 0.22260013 0.72915277 0.59921593 0.63319890
#> [37] 0.76714741 0.41356338 0.94285571 0.80433201 0.85430192 0.51856241
#> [43] 0.56386443 0.83324675 0.77464248 0.15214733 0.63319890 0.82606527
#> [49] 0.87542837 0.68288518 0.87542837 0.63319890 0.62475477 0.35197179
#> [55] 0.91616186 0.74445272 0.83324675 0.85430192 0.78953695 0.19592776
#> [61] 0.31091704 0.99367338 0.68288518 0.09194794 0.37293146 0.09194794
#> [67] 0.19592776 0.61624602 0.59040467 0.15214733 0.43346358 0.51856241
#> [73] 0.69884937 0.94285571 0.36253696 0.98101357 0.31091704 0.89591087
#> [79] 0.74445272 0.02524390 0.58151848 0.09194794 0.59921593 0.29845957
#> [85] 0.56386443 0.13684059 0.91616186 0.93621617 0.67467058 0.49974782
#> [91] 0.89591087 0.40359357 0.27216941 0.28548151 0.54572767 0.18095812
#> [97] 0.51856241 0.47137372 0.06569652 0.94285571 0.31091704 0.49023228
#> [103] 0.98101357 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 18 68 101 88 18.1 179 18.2 177 55 76 66 39 70
#> 15.21 20.62 9.97 18.37 15.21 18.63 15.21 12.53 19.34 19.22 22.13 15.59 7.38
#> 52 16 66.1 43 43.1 105 70.1 55.1 13 184 42 66.2 128
#> 10.42 8.71 22.13 12.10 12.10 19.75 7.38 19.34 14.34 17.77 12.43 22.13 20.35
#> 159 180 39.1 145 25 139 66.3 180.1 79 6 60 166 70.2
#> 10.55 14.82 15.59 10.07 6.32 21.49 22.13 14.82 16.23 15.64 13.15 19.98 7.38
#> 49 10 108 110 159.1 177.1 15 6.1 107 145.1 29 145.2 6.2
#> 12.19 10.53 18.29 17.56 10.55 12.53 22.68 15.64 11.18 10.07 15.45 10.07 15.64
#> 26 36 187 96 159.2 10.1 37 194 139.1 127 29.1 69 68.1
#> 15.77 21.19 9.92 14.54 10.55 10.53 12.52 22.40 21.49 3.53 15.45 23.23 20.62
#> 69.1 194.1 188 5 15.1 58 108.1 18.3 70.3 90 91 139.2 101.1
#> 23.23 22.40 16.16 16.43 22.68 19.34 18.29 15.21 7.38 20.94 5.33 21.49 9.97
#> 96.1 78 23 69.2 79.1 197 110.1 63 187.1 149 167 88.1 101.2
#> 14.54 23.88 16.92 23.23 16.23 21.60 17.56 22.77 9.92 8.37 15.55 18.37 9.97
#> 158 175 136 41 169 108.2 179.1 129 70.4 139.3 8 91.1 193
#> 20.14 21.91 21.83 18.02 22.41 18.29 18.63 23.41 7.38 21.49 18.43 5.33 24.00
#> 98 135 122 143 38 165 176 98.1 75 47 104 147 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 148 137 132 112 48 173 104.1 104.2 3 35 120 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 11 147.1 118 162 34.1 138 82 144 131 2 162.1 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 196 75.1 148.1 38.1 20 53.1 44 21 122.1 31 138.1 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 185 71 122.2 162.2 200 186 64 178 7.1 67 94 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.3 137.1 142 118.1 65 186.1 83.1 28 46.1 48.1 19.1 135.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 65.1 47.1 147.2 21.1 11.1 11.2 135.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[6]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008494627 0.871925738 0.446785832
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.33533652 0.02791375 0.06673686
#> grade_iii, Cure model
#> 0.70947693
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 41 18.02 1 40 1 0
#> 81 14.06 1 34 0 0
#> 133 14.65 1 57 0 0
#> 92 22.92 1 47 0 1
#> 15 22.68 1 48 0 0
#> 15.1 22.68 1 48 0 0
#> 105 19.75 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 175 21.91 1 43 0 0
#> 90 20.94 1 50 0 1
#> 25 6.32 1 34 1 0
#> 129 23.41 1 53 1 0
#> 41.1 18.02 1 40 1 0
#> 86 23.81 1 58 0 1
#> 133.1 14.65 1 57 0 0
#> 52 10.42 1 52 0 1
#> 23 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 32 20.90 1 37 1 0
#> 194 22.40 1 38 0 1
#> 181 16.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 89 11.44 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 134 17.81 1 47 1 0
#> 149 8.37 1 33 1 0
#> 149.1 8.37 1 33 1 0
#> 177 12.53 1 75 0 0
#> 108 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 43 12.10 1 61 0 1
#> 133.2 14.65 1 57 0 0
#> 170 19.54 1 43 0 1
#> 70 7.38 1 30 1 0
#> 49 12.19 1 48 1 0
#> 180 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 125.1 15.65 1 67 1 0
#> 70.1 7.38 1 30 1 0
#> 78 23.88 1 43 0 0
#> 70.2 7.38 1 30 1 0
#> 60 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 6 15.64 1 39 0 0
#> 24 23.89 1 38 0 0
#> 23.1 16.92 1 61 0 0
#> 23.2 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 199 19.81 1 NA 0 1
#> 197 21.60 1 69 1 0
#> 134.1 17.81 1 47 1 0
#> 107 11.18 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 128 20.35 1 35 0 1
#> 69 23.23 1 25 0 1
#> 16 8.71 1 71 0 1
#> 170.1 19.54 1 43 0 1
#> 127 3.53 1 62 0 1
#> 24.1 23.89 1 38 0 0
#> 134.2 17.81 1 47 1 0
#> 159 10.55 1 50 0 1
#> 106 16.67 1 49 1 0
#> 68 20.62 1 44 0 0
#> 175.1 21.91 1 43 0 0
#> 123 13.00 1 44 1 0
#> 69.1 23.23 1 25 0 1
#> 13.1 14.34 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 124.2 9.73 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 199.1 19.81 1 NA 0 1
#> 15.2 22.68 1 48 0 0
#> 41.2 18.02 1 40 1 0
#> 124.3 9.73 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 106.1 16.67 1 49 1 0
#> 43.1 12.10 1 61 0 1
#> 184 17.77 1 38 0 0
#> 6.1 15.64 1 39 0 0
#> 124.4 9.73 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 18 15.21 1 49 1 0
#> 199.2 19.81 1 NA 0 1
#> 52.1 10.42 1 52 0 1
#> 86.1 23.81 1 58 0 1
#> 180.1 14.82 1 37 0 0
#> 49.1 12.19 1 48 1 0
#> 4 17.64 1 NA 0 1
#> 105.1 19.75 1 60 0 0
#> 77.1 7.27 1 67 0 1
#> 190 20.81 1 42 1 0
#> 45 17.42 1 54 0 1
#> 175.2 21.91 1 43 0 0
#> 192 16.44 1 31 1 0
#> 168 23.72 1 70 0 0
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 194.1 22.40 1 38 0 1
#> 58 19.34 1 39 0 0
#> 61 10.12 1 36 0 1
#> 113 22.86 1 34 0 0
#> 158 20.14 1 74 1 0
#> 155 13.08 1 26 0 0
#> 18.1 15.21 1 49 1 0
#> 41.3 18.02 1 40 1 0
#> 71 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 38 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 151 24.00 0 42 0 0
#> 131 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 112 24.00 0 61 0 0
#> 84 24.00 0 39 0 1
#> 152 24.00 0 36 0 1
#> 104.1 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 74 24.00 0 43 0 1
#> 161 24.00 0 45 0 0
#> 160 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 196 24.00 0 19 0 0
#> 9.1 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 9.2 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 142.1 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 148 24.00 0 61 1 0
#> 131.1 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 48 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 148.1 24.00 0 61 1 0
#> 142.2 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 185.2 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 75 24.00 0 21 1 0
#> 131.2 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 196.1 24.00 0 19 0 0
#> 2 24.00 0 9 0 0
#> 64 24.00 0 43 0 0
#> 152.1 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 67.1 24.00 0 25 0 0
#> 38.2 24.00 0 31 1 0
#> 152.2 24.00 0 36 0 1
#> 152.3 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 200 24.00 0 64 0 0
#> 54 24.00 0 53 1 0
#> 7 24.00 0 37 1 0
#> 38.3 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 191 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 173.1 24.00 0 19 0 1
#> 178 24.00 0 52 1 0
#> 62.1 24.00 0 71 0 0
#> 185.3 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 67.2 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 54.1 24.00 0 53 1 0
#> 21 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 126 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 87 24.00 0 27 0 0
#> 191.1 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 185.4 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 94.1 24.00 0 51 0 1
#> 174 24.00 0 49 1 0
#> 151.1 24.00 0 42 0 0
#> 2.1 24.00 0 9 0 0
#> 33 24.00 0 53 0 0
#> 151.2 24.00 0 42 0 0
#> 148.2 24.00 0 61 1 0
#> 83.1 24.00 0 6 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.34 NA NA NA
#> 2 age, Cure model 0.0279 NA NA NA
#> 3 grade_ii, Cure model 0.0667 NA NA NA
#> 4 grade_iii, Cure model 0.709 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00849 NA NA NA
#> 2 grade_ii, Survival model 0.872 NA NA NA
#> 3 grade_iii, Survival model 0.447 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.33534 0.02791 0.06674 0.70948
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 246.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.33533652 0.02791375 0.06673686 0.70947693
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008494627 0.871925738 0.446785832
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.82140809 0.66076155 0.87412420 0.84817502 0.33805143 0.37064585
#> [7] 0.37064585 0.59998155 0.79914427 0.45539019 0.52939824 0.98790861
#> [13] 0.28410565 0.66076155 0.20954321 0.84817502 0.93671198 0.73098881
#> [19] 0.89443082 0.54046663 0.41433078 0.76923480 0.95005634 0.49370657
#> [25] 0.69016339 0.95880239 0.95880239 0.89935262 0.65239149 0.97973743
#> [31] 0.91375338 0.84817502 0.61791846 0.96732423 0.90425054 0.83757996
#> [37] 0.78735270 0.79914427 0.96732423 0.16517363 0.96732423 0.87927350
#> [43] 0.86383569 0.81030621 0.08006794 0.73098881 0.73098881 0.76301943
#> [49] 0.51799844 0.69016339 0.92309833 0.49370657 0.58100901 0.79327850
#> [55] 0.57117451 0.30384956 0.95444797 0.61791846 0.99599625 0.08006794
#> [61] 0.69016339 0.93218717 0.75051613 0.56114936 0.45539019 0.88942788
#> [67] 0.30384956 0.86383569 0.76923480 0.44172082 0.37064585 0.66076155
#> [73] 0.64389308 0.75051613 0.91375338 0.71064671 0.81030621 0.92309833
#> [79] 0.82693517 0.93671198 0.20954321 0.83757996 0.90425054 0.59998155
#> [85] 0.97973743 0.55104239 0.72429843 0.45539019 0.78136329 0.25969789
#> [91] 0.71751576 0.99196582 0.41433078 0.63522616 0.94561688 0.35447399
#> [97] 0.59076043 0.88435429 0.82693517 0.66076155 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 39 41 81 133 92 15 15.1 105 125 175 90 25 129
#> 15.59 18.02 14.06 14.65 22.92 22.68 22.68 19.75 15.65 21.91 20.94 6.32 23.41
#> 41.1 86 133.1 52 23 140 32 194 181 187 136 134 149
#> 18.02 23.81 14.65 10.42 16.92 12.68 20.90 22.40 16.46 9.92 21.83 17.81 8.37
#> 149.1 177 108 77 43 133.2 170 70 49 180 5 125.1 70.1
#> 8.37 12.53 18.29 7.27 12.10 14.65 19.54 7.38 12.19 14.82 16.43 15.65 7.38
#> 78 70.2 60 13 6 24 23.1 23.2 171 197 134.1 107 136.1
#> 23.88 7.38 13.15 14.34 15.64 23.89 16.92 16.92 16.57 21.60 17.81 11.18 21.83
#> 150 26 128 69 16 170.1 127 24.1 134.2 159 106 68 175.1
#> 20.33 15.77 20.35 23.23 8.71 19.54 3.53 23.89 17.81 10.55 16.67 20.62 21.91
#> 123 69.1 13.1 181.1 66 15.2 41.2 76 106.1 43.1 184 6.1 107.1
#> 13.00 23.23 14.34 16.46 22.13 22.68 18.02 19.22 16.67 12.10 17.77 15.64 11.18
#> 18 52.1 86.1 180.1 49.1 105.1 77.1 190 45 175.2 192 168 111
#> 15.21 10.42 23.81 14.82 12.19 19.75 7.27 20.81 17.42 21.91 16.44 23.72 17.45
#> 91 194.1 58 61 113 158 155 18.1 41.3 71 173 53 38
#> 5.33 22.40 19.34 10.12 22.86 20.14 13.08 15.21 18.02 24.00 24.00 24.00 24.00
#> 185 9 198 151 131 185.1 104 65 98 112 84 152 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 74 161 160 142 196 9.1 38.1 9.2 67 142.1 11 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 94 48 47 148.1 142.2 12 185.2 144 75 131.2 62 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 196.1 2 64 152.1 3 67.1 38.2 152.2 152.3 146 200 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 38.3 20 191 17 173.1 178 62.1 185.3 121 67.2 72 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 126 156 83 87 191.1 165 185.4 132 94.1 174 151.1 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 151.2 148.2 83.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[7]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00918627 0.38180550 -0.17167512
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.42045141 0.03085011 0.04521886
#> grade_iii, Cure model
#> 0.37193102
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 164 23.60 1 76 0 1
#> 111 17.45 1 47 0 1
#> 179 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 133 14.65 1 57 0 0
#> 184 17.77 1 38 0 0
#> 179.1 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 93 10.33 1 52 0 1
#> 177 12.53 1 75 0 0
#> 78 23.88 1 43 0 0
#> 167 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 41 18.02 1 40 1 0
#> 49 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 105 19.75 1 60 0 0
#> 10 10.53 1 34 0 0
#> 70 7.38 1 30 1 0
#> 30 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 16 8.71 1 71 0 1
#> 30.1 17.43 1 78 0 0
#> 188 16.16 1 46 0 1
#> 164.1 23.60 1 76 0 1
#> 136 21.83 1 43 0 1
#> 129 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 150 20.33 1 48 0 0
#> 171 16.57 1 41 0 1
#> 183.1 9.24 1 67 1 0
#> 69 23.23 1 25 0 1
#> 106 16.67 1 49 1 0
#> 190 20.81 1 42 1 0
#> 89 11.44 1 NA 0 0
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 181 16.46 1 45 0 1
#> 50.1 10.02 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 171.1 16.57 1 41 0 1
#> 177.1 12.53 1 75 0 0
#> 50.2 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 61 10.12 1 36 0 1
#> 59 10.16 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 18 15.21 1 49 1 0
#> 6 15.64 1 39 0 0
#> 76.1 19.22 1 54 0 1
#> 99 21.19 1 38 0 1
#> 58 19.34 1 39 0 0
#> 78.1 23.88 1 43 0 0
#> 42 12.43 1 49 0 1
#> 194.1 22.40 1 38 0 1
#> 159 10.55 1 50 0 1
#> 108 18.29 1 39 0 1
#> 195.1 11.76 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 140 12.68 1 59 1 0
#> 92 22.92 1 47 0 1
#> 155 13.08 1 26 0 0
#> 50.3 10.02 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 25 6.32 1 34 1 0
#> 101 9.97 1 10 0 1
#> 140.1 12.68 1 59 1 0
#> 127 3.53 1 62 0 1
#> 188.1 16.16 1 46 0 1
#> 154 12.63 1 20 1 0
#> 188.2 16.16 1 46 0 1
#> 89.1 11.44 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 32 20.90 1 37 1 0
#> 76.2 19.22 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 81.1 14.06 1 34 0 0
#> 85 16.44 1 36 0 0
#> 99.1 21.19 1 38 0 1
#> 100 16.07 1 60 0 0
#> 195.2 11.76 1 NA 1 0
#> 171.2 16.57 1 41 0 1
#> 139 21.49 1 63 1 0
#> 92.1 22.92 1 47 0 1
#> 76.3 19.22 1 54 0 1
#> 86 23.81 1 58 0 1
#> 51.1 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 88 18.37 1 47 0 0
#> 66 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 79.1 16.23 1 54 1 0
#> 194.2 22.40 1 38 0 1
#> 86.1 23.81 1 58 0 1
#> 107 11.18 1 54 1 0
#> 10.1 10.53 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 190.1 20.81 1 42 1 0
#> 57.1 14.46 1 45 0 1
#> 105.1 19.75 1 60 0 0
#> 155.1 13.08 1 26 0 0
#> 153 21.33 1 55 1 0
#> 164.2 23.60 1 76 0 1
#> 89.2 11.44 1 NA 0 0
#> 157.1 15.10 1 47 0 0
#> 156 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 27 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 31 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 94.1 24.00 0 51 0 1
#> 142.1 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 22 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 47.1 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 198 24.00 0 66 0 1
#> 47.2 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 182 24.00 0 35 0 0
#> 27.1 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 151 24.00 0 42 0 0
#> 3 24.00 0 31 1 0
#> 142.2 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 12 24.00 0 63 0 0
#> 83.1 24.00 0 6 0 0
#> 144 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 87.1 24.00 0 27 0 0
#> 104 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 104.1 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 7 24.00 0 37 1 0
#> 160.1 24.00 0 31 1 0
#> 94.2 24.00 0 51 0 1
#> 83.2 24.00 0 6 0 0
#> 17.1 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 87.2 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 11.1 24.00 0 42 0 1
#> 193 24.00 0 45 0 1
#> 126 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 126.1 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 109.1 24.00 0 48 0 0
#> 173.1 24.00 0 19 0 1
#> 191 24.00 0 60 0 1
#> 198.1 24.00 0 66 0 1
#> 143 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#> 163.1 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 156.1 24.00 0 50 1 0
#> 64 24.00 0 43 0 0
#> 148.1 24.00 0 61 1 0
#> 84.2 24.00 0 39 0 1
#> 104.2 24.00 0 50 1 0
#> 44 24.00 0 56 0 0
#> 38 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 3.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 31.1 24.00 0 36 0 1
#> 142.3 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 83.3 24.00 0 6 0 0
#> 176 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.42 NA NA NA
#> 2 age, Cure model 0.0309 NA NA NA
#> 3 grade_ii, Cure model 0.0452 NA NA NA
#> 4 grade_iii, Cure model 0.372 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00919 NA NA NA
#> 2 grade_ii, Survival model 0.382 NA NA NA
#> 3 grade_iii, Survival model -0.172 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.42045 0.03085 0.04522 0.37193
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 247.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.42045141 0.03085011 0.04521886 0.37193102
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00918627 0.38180550 -0.17167512
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0070582028 0.3046409669 0.2160012769 0.6048697631 0.5922365796
#> [6] 0.2943156770 0.2160012769 0.7746625202 0.5427928940 0.8710954788
#> [11] 0.7345753154 0.0006795372 0.5305319669 0.2538604353 0.2738943557
#> [16] 0.7882777281 0.9136604225 0.0811768523 0.1566607310 0.8433146054
#> [21] 0.9565938546 0.3151273034 0.0500040747 0.9421275176 0.3151273034
#> [26] 0.4709633750 0.0070582028 0.0742211560 0.0162665921 0.1814477589
#> [31] 0.1486466678 0.3691954314 0.9136604225 0.0203211367 0.3474616453
#> [36] 0.1333368946 0.0339541352 0.5674528831 0.4025367748 0.3364656688
#> [41] 0.3691954314 0.7345753154 0.1175489026 0.8852068123 0.0339541352
#> [46] 0.8019064583 0.0442624771 0.5551138401 0.5183061450 0.1814477589
#> [51] 0.1027218795 0.1729686029 0.0006795372 0.7611479629 0.0500040747
#> [56] 0.8294316019 0.2441144952 0.4141180901 0.6952040955 0.0246642168
#> [61] 0.6560867464 0.3474616453 0.9710357214 0.8994075481 0.6952040955
#> [66] 0.9854621565 0.4709633750 0.7214060399 0.4709633750 0.6303386585
#> [71] 0.1254534439 0.1814477589 0.6303386585 0.4141180901 0.1027218795
#> [76] 0.5061665554 0.3691954314 0.0882682184 0.0246642168 0.1814477589
#> [81] 0.0029983292 0.2538604353 0.2840960575 0.4479725493 0.2345260552
#> [86] 0.0675367053 0.6820514328 0.4479725493 0.0500040747 0.0029983292
#> [91] 0.8156564917 0.8433146054 0.4141180901 0.1333368946 0.6048697631
#> [96] 0.1566607310 0.6560867464 0.0954631685 0.0070582028 0.5674528831
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 164 111 179 57 133 184 179.1 56 29 93 177 78 167
#> 23.60 17.45 18.63 14.46 14.65 17.77 18.63 12.21 15.45 10.33 12.53 23.88 15.55
#> 51 41 49 183 197 105 10 70 30 194 16 30.1 188
#> 18.23 18.02 12.19 9.24 21.60 19.75 10.53 7.38 17.43 22.40 8.71 17.43 16.16
#> 164.1 136 129 76 150 171 183.1 69 106 190 15 157 181
#> 23.60 21.83 23.41 19.22 20.33 16.57 9.24 23.23 16.67 20.81 22.68 15.10 16.46
#> 23 171.1 177.1 90 61 15.1 43 169 18 6 76.1 99 58
#> 16.92 16.57 12.53 20.94 10.12 22.68 12.10 22.41 15.21 15.64 19.22 21.19 19.34
#> 78.1 42 194.1 159 108 192 140 92 155 106.1 25 101 140.1
#> 23.88 12.43 22.40 10.55 18.29 16.44 12.68 22.92 13.08 16.67 6.32 9.97 12.68
#> 127 188.1 154 188.2 81 32 76.2 81.1 85 99.1 100 171.2 139
#> 3.53 16.16 12.63 16.16 14.06 20.90 19.22 14.06 16.44 21.19 16.07 16.57 21.49
#> 92.1 76.3 86 51.1 134 79 88 66 14 79.1 194.2 86.1 107
#> 22.92 19.22 23.81 18.23 17.81 16.23 18.37 22.13 12.89 16.23 22.40 23.81 11.18
#> 10.1 192.1 190.1 57.1 105.1 155.1 153 164.2 157.1 156 142 27 152
#> 10.53 16.44 20.81 14.46 19.75 13.08 21.33 23.60 15.10 24.00 24.00 24.00 24.00
#> 163 17 94 47 84 137 83 31 62 94.1 142.1 87 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 131 132 47.1 53 172 67 198 47.2 116 122 119 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 148 151 3 142.2 186 12 83.1 144 54 87.1 104 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 104.1 173 7 160.1 94.2 83.2 17.1 11 87.2 11.1 193 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 126.1 172.1 109.1 173.1 191 198.1 143 53.1 163.1 119.1 156.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 84.2 104.2 44 38 173.2 3.1 162 21 9 75 31.1 142.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 185 83.3 176 20
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[8]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002074206 0.971390269 0.726706589
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.48651830 -0.01444081 0.24322940
#> grade_iii, Cure model
#> 1.05250325
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 169 22.41 1 46 0 0
#> 183 9.24 1 67 1 0
#> 45 17.42 1 54 0 1
#> 190 20.81 1 42 1 0
#> 63 22.77 1 31 1 0
#> 187 9.92 1 39 1 0
#> 123 13.00 1 44 1 0
#> 125 15.65 1 67 1 0
#> 117 17.46 1 26 0 1
#> 99 21.19 1 38 0 1
#> 127 3.53 1 62 0 1
#> 195 11.76 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 88 18.37 1 47 0 0
#> 25 6.32 1 34 1 0
#> 89 11.44 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 25.1 6.32 1 34 1 0
#> 42 12.43 1 49 0 1
#> 134 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 194 22.40 1 38 0 1
#> 107 11.18 1 54 1 0
#> 129 23.41 1 53 1 0
#> 192 16.44 1 31 1 0
#> 155 13.08 1 26 0 0
#> 158 20.14 1 74 1 0
#> 32 20.90 1 37 1 0
#> 41 18.02 1 40 1 0
#> 70 7.38 1 30 1 0
#> 70.1 7.38 1 30 1 0
#> 42.1 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 55 19.34 1 69 0 1
#> 168 23.72 1 70 0 0
#> 8 18.43 1 32 0 0
#> 24 23.89 1 38 0 0
#> 153 21.33 1 55 1 0
#> 6 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 14 12.89 1 21 0 0
#> 45.1 17.42 1 54 0 1
#> 110 17.56 1 65 0 1
#> 6.1 15.64 1 39 0 0
#> 134.1 17.81 1 47 1 0
#> 78.1 23.88 1 43 0 0
#> 60 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 100 16.07 1 60 0 0
#> 13 14.34 1 54 0 1
#> 5 16.43 1 51 0 1
#> 183.1 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 29 15.45 1 68 1 0
#> 184 17.77 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 96 14.54 1 33 0 1
#> 26 15.77 1 49 0 1
#> 113 22.86 1 34 0 0
#> 58 19.34 1 39 0 0
#> 63.1 22.77 1 31 1 0
#> 79 16.23 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 97 19.14 1 65 0 1
#> 195.1 11.76 1 NA 1 0
#> 110.1 17.56 1 65 0 1
#> 58.1 19.34 1 39 0 0
#> 57 14.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 125.1 15.65 1 67 1 0
#> 130.1 16.47 1 53 0 1
#> 166 19.98 1 48 0 0
#> 124.1 9.73 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 41.1 18.02 1 40 1 0
#> 99.1 21.19 1 38 0 1
#> 55.1 19.34 1 69 0 1
#> 36 21.19 1 48 0 1
#> 170 19.54 1 43 0 1
#> 86 23.81 1 58 0 1
#> 70.2 7.38 1 30 1 0
#> 37 12.52 1 57 1 0
#> 14.1 12.89 1 21 0 0
#> 4 17.64 1 NA 0 1
#> 41.2 18.02 1 40 1 0
#> 25.2 6.32 1 34 1 0
#> 45.2 17.42 1 54 0 1
#> 41.3 18.02 1 40 1 0
#> 78.2 23.88 1 43 0 0
#> 76 19.22 1 54 0 1
#> 153.1 21.33 1 55 1 0
#> 108.1 18.29 1 39 0 1
#> 140 12.68 1 59 1 0
#> 88.1 18.37 1 47 0 0
#> 6.2 15.64 1 39 0 0
#> 88.2 18.37 1 47 0 0
#> 90 20.94 1 50 0 1
#> 55.2 19.34 1 69 0 1
#> 60.1 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 18 15.21 1 49 1 0
#> 77 7.27 1 67 0 1
#> 107.1 11.18 1 54 1 0
#> 100.1 16.07 1 60 0 0
#> 124.2 9.73 1 NA 1 0
#> 121 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 46 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 17 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 20 24.00 0 46 1 0
#> 82 24.00 0 34 0 0
#> 103 24.00 0 56 1 0
#> 161 24.00 0 45 0 0
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 176 24.00 0 43 0 1
#> 132 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 131.1 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 103.1 24.00 0 56 1 0
#> 198 24.00 0 66 0 1
#> 21 24.00 0 47 0 0
#> 182 24.00 0 35 0 0
#> 33 24.00 0 53 0 0
#> 109 24.00 0 48 0 0
#> 82.1 24.00 0 34 0 0
#> 1 24.00 0 23 1 0
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 12 24.00 0 63 0 0
#> 65.2 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 65.3 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 82.2 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 147 24.00 0 76 1 0
#> 94 24.00 0 51 0 1
#> 121.1 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 73 24.00 0 NA 0 1
#> 122 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 185 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 3 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 33.1 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 148.1 24.00 0 61 1 0
#> 44.1 24.00 0 56 0 0
#> 198.1 24.00 0 66 0 1
#> 62.1 24.00 0 71 0 0
#> 185.2 24.00 0 44 1 0
#> 65.4 24.00 0 57 1 0
#> 1.1 24.00 0 23 1 0
#> 178.1 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 67.1 24.00 0 25 0 0
#> 143.1 24.00 0 51 0 0
#> 193.1 24.00 0 45 0 1
#> 11.1 24.00 0 42 0 1
#> 132.1 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 75.1 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 109.1 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 200 24.00 0 64 0 0
#> 163 24.00 0 66 0 0
#> 182.1 24.00 0 35 0 0
#> 38.1 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 33.2 24.00 0 53 0 0
#> 131.2 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.487 NA NA NA
#> 2 age, Cure model -0.0144 NA NA NA
#> 3 grade_ii, Cure model 0.243 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00207 NA NA NA
#> 2 grade_ii, Survival model 0.971 NA NA NA
#> 3 grade_iii, Survival model 0.727 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.48652 -0.01444 0.24323 1.05250
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 253.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.48651830 -0.01444081 0.24322940 1.05250325
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002074206 0.971390269 0.726706589
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.06963214 0.29579772 0.93897779 0.68748029 0.43274212 0.25183303
#> [7] 0.92730400 0.86592685 0.78022418 0.67985608 0.37780947 0.99460046
#> [13] 0.32523851 0.44306865 0.92134045 0.75241347 0.56493220 0.97841810
#> [19] 0.95046607 0.97841810 0.89720347 0.64107130 0.45341622 0.31083556
#> [25] 0.90938099 0.17933240 0.72397571 0.85956467 0.46355024 0.42205312
#> [31] 0.60917549 0.95620039 0.95620039 0.89720347 0.70948553 0.49299588
#> [37] 0.15634852 0.55591038 0.02359930 0.35342490 0.79371523 0.28082929
#> [43] 0.87222374 0.68748029 0.66452915 0.79371523 0.64107130 0.06963214
#> [49] 0.84689230 0.19889664 0.75938469 0.84039149 0.73826498 0.93897779
#> [55] 0.33970827 0.81390542 0.65667386 0.02359930 0.82725822 0.77329290
#> [61] 0.21691088 0.49299588 0.25183303 0.74538493 0.21691088 0.59168511
#> [67] 0.54689796 0.66452915 0.49299588 0.83384771 0.78022418 0.70948553
#> [73] 0.47341142 0.92730400 0.60917549 0.37780947 0.49299588 0.37780947
#> [79] 0.48329210 0.13381735 0.95620039 0.89102079 0.87222374 0.60917549
#> [85] 0.97841810 0.68748029 0.60917549 0.06963214 0.53776401 0.35342490
#> [91] 0.59168511 0.88477978 0.56493220 0.79371523 0.56493220 0.41095768
#> [97] 0.49299588 0.84689230 0.72397571 0.82061947 0.97285882 0.90938099
#> [103] 0.75938469 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 78 169 183 45 190 63 187 123 125 117 99 127 66
#> 23.88 22.41 9.24 17.42 20.81 22.77 9.92 13.00 15.65 17.46 21.19 3.53 22.13
#> 68 61 188 88 25 16 25.1 42 134 128 194 107 129
#> 20.62 10.12 16.16 18.37 6.32 8.71 6.32 12.43 17.81 20.35 22.40 11.18 23.41
#> 192 155 158 32 41 70 70.1 42.1 130 55 168 8 24
#> 16.44 13.08 20.14 20.90 18.02 7.38 7.38 12.43 16.47 19.34 23.72 18.43 23.89
#> 153 6 15 14 45.1 110 6.1 134.1 78.1 60 92 100 13
#> 21.33 15.64 22.68 12.89 17.42 17.56 15.64 17.81 23.88 13.15 22.92 16.07 14.34
#> 5 183.1 197 29 184 24.1 96 26 113 58 63.1 79 113.1
#> 16.43 9.24 21.60 15.45 17.77 23.89 14.54 15.77 22.86 19.34 22.77 16.23 22.86
#> 108 97 110.1 58.1 57 125.1 130.1 166 187.1 41.1 99.1 55.1 36
#> 18.29 19.14 17.56 19.34 14.46 15.65 16.47 19.98 9.92 18.02 21.19 19.34 21.19
#> 170 86 70.2 37 14.1 41.2 25.2 45.2 41.3 78.2 76 153.1 108.1
#> 19.54 23.81 7.38 12.52 12.89 18.02 6.32 17.42 18.02 23.88 19.22 21.33 18.29
#> 140 88.1 6.2 88.2 90 55.2 60.1 85 18 77 107.1 100.1 121
#> 12.68 18.37 15.64 18.37 20.94 19.34 13.15 16.44 15.21 7.27 11.18 16.07 24.00
#> 191 186 54 131 65 65.1 46 38 64 17 44 20 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 161 160 174 176 132 193 131.1 138 75 103.1 198 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 33 109 82.1 1 11 48 160.1 67 12 65.2 178 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.3 62 82.2 116 147 94 121.1 28 122 84 185 47 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 143 185.1 33.1 148 148.1 44.1 198.1 62.1 185.2 65.4 1.1 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 67.1 143.1 193.1 11.1 132.1 141 162 172 75.1 34 109.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 163 182.1 38.1 146 162.1 33.2 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[9]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003004424 0.695560764 0.332684223
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.42592018 0.02897092 -0.15708574
#> grade_iii, Cure model
#> 0.68023591
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 69 23.23 1 25 0 1
#> 78 23.88 1 43 0 0
#> 188 16.16 1 46 0 1
#> 166 19.98 1 48 0 0
#> 97 19.14 1 65 0 1
#> 6 15.64 1 39 0 0
#> 77 7.27 1 67 0 1
#> 51 18.23 1 83 0 1
#> 125 15.65 1 67 1 0
#> 79 16.23 1 54 1 0
#> 158 20.14 1 74 1 0
#> 167 15.55 1 56 1 0
#> 57 14.46 1 45 0 1
#> 97.1 19.14 1 65 0 1
#> 23 16.92 1 61 0 0
#> 61 10.12 1 36 0 1
#> 93 10.33 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 78.1 23.88 1 43 0 0
#> 70 7.38 1 30 1 0
#> 154 12.63 1 20 1 0
#> 93.1 10.33 1 52 0 1
#> 99 21.19 1 38 0 1
#> 129 23.41 1 53 1 0
#> 56 12.21 1 60 0 0
#> 127 3.53 1 62 0 1
#> 16 8.71 1 71 0 1
#> 190 20.81 1 42 1 0
#> 169 22.41 1 46 0 0
#> 90 20.94 1 50 0 1
#> 164 23.60 1 76 0 1
#> 50.1 10.02 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 29 15.45 1 68 1 0
#> 164.1 23.60 1 76 0 1
#> 190.1 20.81 1 42 1 0
#> 117 17.46 1 26 0 1
#> 110 17.56 1 65 0 1
#> 167.2 15.55 1 56 1 0
#> 50.2 10.02 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 76.1 19.22 1 54 0 1
#> 153 21.33 1 55 1 0
#> 123.1 13.00 1 44 1 0
#> 15 22.68 1 48 0 0
#> 88 18.37 1 47 0 0
#> 30 17.43 1 78 0 0
#> 61.1 10.12 1 36 0 1
#> 39 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 184 17.77 1 38 0 0
#> 133 14.65 1 57 0 0
#> 194 22.40 1 38 0 1
#> 37 12.52 1 57 1 0
#> 136.1 21.83 1 43 0 1
#> 192 16.44 1 31 1 0
#> 14 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 79.1 16.23 1 54 1 0
#> 168 23.72 1 70 0 0
#> 130 16.47 1 53 0 1
#> 130.1 16.47 1 53 0 1
#> 114.1 13.68 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 140.1 12.68 1 59 1 0
#> 153.1 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 50.3 10.02 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 111 17.45 1 47 0 1
#> 194.1 22.40 1 38 0 1
#> 111.1 17.45 1 47 0 1
#> 69.1 23.23 1 25 0 1
#> 181 16.46 1 45 0 1
#> 199.1 19.81 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 153.2 21.33 1 55 1 0
#> 4.1 17.64 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 50.4 10.02 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 108 18.29 1 39 0 1
#> 197 21.60 1 69 1 0
#> 4.2 17.64 1 NA 0 1
#> 145.1 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 88.1 18.37 1 47 0 0
#> 66.1 22.13 1 53 0 0
#> 58 19.34 1 39 0 0
#> 139.1 21.49 1 63 1 0
#> 175 21.91 1 43 0 0
#> 125.1 15.65 1 67 1 0
#> 85.1 16.44 1 36 0 0
#> 92 22.92 1 47 0 1
#> 194.2 22.40 1 38 0 1
#> 91 5.33 1 61 0 1
#> 90.1 20.94 1 50 0 1
#> 188.1 16.16 1 46 0 1
#> 4.3 17.64 1 NA 0 1
#> 174 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 87 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 144 24.00 0 28 0 1
#> 144.1 24.00 0 28 0 1
#> 176 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 9 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 173.1 24.00 0 19 0 1
#> 198 24.00 0 66 0 1
#> 131.1 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 46.1 24.00 0 71 0 0
#> 94 24.00 0 51 0 1
#> 176.1 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 27.1 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 7 24.00 0 37 1 0
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 191 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 151 24.00 0 42 0 0
#> 103 24.00 0 56 1 0
#> 73 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 54.1 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 126.1 24.00 0 48 0 0
#> 198.1 24.00 0 66 0 1
#> 75.1 24.00 0 21 1 0
#> 17.1 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#> 147 24.00 0 76 1 0
#> 132 24.00 0 55 0 0
#> 178 24.00 0 52 1 0
#> 73.1 24.00 0 NA 0 1
#> 17.2 24.00 0 38 0 1
#> 54.2 24.00 0 53 1 0
#> 178.1 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 143 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 151.1 24.00 0 42 0 0
#> 141 24.00 0 44 1 0
#> 75.2 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 27.2 24.00 0 63 1 0
#> 9.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 31.1 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 174.1 24.00 0 49 1 0
#> 144.2 24.00 0 28 0 1
#> 65 24.00 0 57 1 0
#> 196.1 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 17.3 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 151.2 24.00 0 42 0 0
#> 115 24.00 0 NA 1 0
#> 186.1 24.00 0 45 1 0
#> 138.1 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 17.4 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 151.3 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 11.1 24.00 0 42 0 1
#> 156.1 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.43 NA NA NA
#> 2 age, Cure model 0.0290 NA NA NA
#> 3 grade_ii, Cure model -0.157 NA NA NA
#> 4 grade_iii, Cure model 0.680 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00300 NA NA NA
#> 2 grade_ii, Survival model 0.696 NA NA NA
#> 3 grade_iii, Survival model 0.333 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.42592 0.02897 -0.15709 0.68024
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.5
#> Residual Deviance: 239.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.42592018 0.02897092 -0.15708574 0.68023591
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003004424 0.695560764 0.332684223
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.44786350 0.79795522 0.10306660 0.01263452 0.67168442 0.41775494
#> [7] 0.46760659 0.70860340 0.97553222 0.51686772 0.69030166 0.65295578
#> [13] 0.40778516 0.72702209 0.78023744 0.46760659 0.58557163 0.91757635
#> [19] 0.90077675 0.25541497 0.29233316 0.83265200 0.01263452 0.96735589
#> [25] 0.84976933 0.90077675 0.34634068 0.08836475 0.87532265 0.99185475
#> [31] 0.95082936 0.37775140 0.16814290 0.35699828 0.05819243 0.72702209
#> [37] 0.75356842 0.05819243 0.37775140 0.54657351 0.53668282 0.72702209
#> [43] 0.78909259 0.44786350 0.31511438 0.79795522 0.15476824 0.48722781
#> [49] 0.57577362 0.91757635 0.71782740 0.62449433 0.52676522 0.76245618
#> [55] 0.18165682 0.86683760 0.25541497 0.62449433 0.81529232 0.39766567
#> [61] 0.93429888 0.21747850 0.65295578 0.03942259 0.59539717 0.59539717
#> [67] 0.89230680 0.83265200 0.31511438 0.14154762 0.81529232 0.55641259
#> [73] 0.18165682 0.55641259 0.10306660 0.61476609 0.42775679 0.31511438
#> [79] 0.77136029 0.95912166 0.85829490 0.50695374 0.28006945 0.93429888
#> [85] 0.88382130 0.48722781 0.21747850 0.43779738 0.29233316 0.24248727
#> [91] 0.69030166 0.62449433 0.12844662 0.18165682 0.98369894 0.35699828
#> [97] 0.67168442 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000
#>
#> $Time
#> 76 123 69 78 188 166 97 6 77 51 125 79 158
#> 19.22 13.00 23.23 23.88 16.16 19.98 19.14 15.64 7.27 18.23 15.65 16.23 20.14
#> 167 57 97.1 23 61 93 136 139 140 78.1 70 154 93.1
#> 15.55 14.46 19.14 16.92 10.12 10.33 21.83 21.49 12.68 23.88 7.38 12.63 10.33
#> 99 129 56 127 16 190 169 90 164 167.1 29 164.1 190.1
#> 21.19 23.41 12.21 3.53 8.71 20.81 22.41 20.94 23.60 15.55 15.45 23.60 20.81
#> 117 110 167.2 155 76.1 153 123.1 15 88 30 61.1 39 85
#> 17.46 17.56 15.55 13.08 19.22 21.33 13.00 22.68 18.37 17.43 10.12 15.59 16.44
#> 184 133 194 37 136.1 192 14 150 145 66 79.1 168 130
#> 17.77 14.65 22.40 12.52 21.83 16.44 12.89 20.33 10.07 22.13 16.23 23.72 16.47
#> 130.1 52 140.1 153.1 113 14.1 111 194.1 111.1 69.1 181 105 153.2
#> 16.47 10.42 12.68 21.33 22.86 12.89 17.45 22.40 17.45 23.23 16.46 19.75 21.33
#> 96 149 177 108 197 145.1 43 88.1 66.1 58 139.1 175 125.1
#> 14.54 8.37 12.53 18.29 21.60 10.07 12.10 18.37 22.13 19.34 21.49 21.91 15.65
#> 85.1 92 194.2 91 90.1 188.1 174 173 46 74 33 31 196
#> 16.44 22.92 22.40 5.33 20.94 16.16 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 2 144 144.1 176 126 172 131 156 54 9 118 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 173.1 198 131.1 75 46.1 94 176.1 163 163.1 27.1 17 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 7 186 82 191 182 151 103 11 54.1 22 126.1 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 17.1 119 147 132 178 17.2 54.2 178.1 71 53 143 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 141 75.2 185 27.2 9.1 20 31.1 1 174.1 144.2 65 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 17.3 143.1 151.2 186.1 138.1 104 17.4 200 151.3 102 11.1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[10]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005544737 0.416547623 0.085280668
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91064110 0.01416673 0.58924829
#> grade_iii, Cure model
#> 0.81743345
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 188 16.16 1 46 0 1
#> 192 16.44 1 31 1 0
#> 13 14.34 1 54 0 1
#> 76 19.22 1 54 0 1
#> 79.1 16.23 1 54 1 0
#> 66 22.13 1 53 0 0
#> 5 16.43 1 51 0 1
#> 133 14.65 1 57 0 0
#> 58 19.34 1 39 0 0
#> 43 12.10 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 133.1 14.65 1 57 0 0
#> 139 21.49 1 63 1 0
#> 78 23.88 1 43 0 0
#> 50 10.02 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 134 17.81 1 47 1 0
#> 59.1 10.16 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 57 14.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 107 11.18 1 54 1 0
#> 183 9.24 1 67 1 0
#> 70 7.38 1 30 1 0
#> 52 10.42 1 52 0 1
#> 117 17.46 1 26 0 1
#> 29 15.45 1 68 1 0
#> 177 12.53 1 75 0 0
#> 100 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 16 8.71 1 71 0 1
#> 199 19.81 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 10 10.53 1 34 0 0
#> 184 17.77 1 38 0 0
#> 136 21.83 1 43 0 1
#> 159 10.55 1 50 0 1
#> 92 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 187.1 9.92 1 39 1 0
#> 99 21.19 1 38 0 1
#> 123 13.00 1 44 1 0
#> 56 12.21 1 60 0 0
#> 134.1 17.81 1 47 1 0
#> 40.1 18.00 1 28 1 0
#> 24 23.89 1 38 0 0
#> 125 15.65 1 67 1 0
#> 113 22.86 1 34 0 0
#> 190.1 20.81 1 42 1 0
#> 92.1 22.92 1 47 0 1
#> 139.1 21.49 1 63 1 0
#> 153 21.33 1 55 1 0
#> 58.1 19.34 1 39 0 0
#> 166 19.98 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 158 20.14 1 74 1 0
#> 85 16.44 1 36 0 0
#> 81 14.06 1 34 0 0
#> 157 15.10 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 139.2 21.49 1 63 1 0
#> 179 18.63 1 42 0 0
#> 190.2 20.81 1 42 1 0
#> 50.1 10.02 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 40.2 18.00 1 28 1 0
#> 90 20.94 1 50 0 1
#> 168 23.72 1 70 0 0
#> 63 22.77 1 31 1 0
#> 169 22.41 1 46 0 0
#> 158.1 20.14 1 74 1 0
#> 110 17.56 1 65 0 1
#> 88 18.37 1 47 0 0
#> 113.1 22.86 1 34 0 0
#> 37 12.52 1 57 1 0
#> 88.1 18.37 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 199.2 19.81 1 NA 0 1
#> 166.1 19.98 1 48 0 0
#> 68 20.62 1 44 0 0
#> 49 12.19 1 48 1 0
#> 149 8.37 1 33 1 0
#> 49.1 12.19 1 48 1 0
#> 30 17.43 1 78 0 0
#> 36 21.19 1 48 0 1
#> 69.1 23.23 1 25 0 1
#> 81.1 14.06 1 34 0 0
#> 5.1 16.43 1 51 0 1
#> 195.1 11.76 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 93 10.33 1 52 0 1
#> 13.1 14.34 1 54 0 1
#> 8 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 145 10.07 1 65 1 0
#> 39 15.59 1 37 0 1
#> 93.1 10.33 1 52 0 1
#> 56.1 12.21 1 60 0 0
#> 85.1 16.44 1 36 0 0
#> 177.1 12.53 1 75 0 0
#> 130 16.47 1 53 0 1
#> 36.1 21.19 1 48 0 1
#> 117.1 17.46 1 26 0 1
#> 77 7.27 1 67 0 1
#> 105 19.75 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 164 23.60 1 76 0 1
#> 79.2 16.23 1 54 1 0
#> 119 24.00 0 17 0 0
#> 182 24.00 0 35 0 0
#> 163 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 162 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 27.1 24.00 0 63 1 0
#> 94 24.00 0 51 0 1
#> 22 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 152 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 28 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 119.1 24.00 0 17 0 0
#> 196 24.00 0 19 0 0
#> 48 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 200.1 24.00 0 64 0 0
#> 122 24.00 0 66 0 0
#> 64.1 24.00 0 43 0 0
#> 142 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 119.2 24.00 0 17 0 0
#> 28.1 24.00 0 67 1 0
#> 173.1 24.00 0 19 0 1
#> 112.1 24.00 0 61 0 0
#> 73 24.00 0 NA 0 1
#> 112.2 24.00 0 61 0 0
#> 200.2 24.00 0 64 0 0
#> 200.3 24.00 0 64 0 0
#> 119.3 24.00 0 17 0 0
#> 161.1 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 67 24.00 0 25 0 0
#> 118 24.00 0 44 1 0
#> 112.3 24.00 0 61 0 0
#> 172 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#> 71 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 28.2 24.00 0 67 1 0
#> 121 24.00 0 57 1 0
#> 84.1 24.00 0 39 0 1
#> 73.1 24.00 0 NA 0 1
#> 17.1 24.00 0 38 0 1
#> 17.2 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 137.1 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 151 24.00 0 42 0 0
#> 200.4 24.00 0 64 0 0
#> 165.1 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 144 24.00 0 28 0 1
#> 120 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 196.1 24.00 0 19 0 0
#> 35 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 46.1 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 151.1 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 31.1 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 31.2 24.00 0 36 0 1
#> 74.2 24.00 0 43 0 1
#> 112.4 24.00 0 61 0 0
#> 143.1 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 151.2 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.911 NA NA NA
#> 2 age, Cure model 0.0142 NA NA NA
#> 3 grade_ii, Cure model 0.589 NA NA NA
#> 4 grade_iii, Cure model 0.817 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00554 NA NA NA
#> 2 grade_ii, Survival model 0.417 NA NA NA
#> 3 grade_iii, Survival model 0.0853 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91064 0.01417 0.58925 0.81743
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 252 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91064110 0.01416673 0.58924829 0.81743345
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005544737 0.416547623 0.085280668
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.69237425 0.71487129 0.65323467 0.80917225 0.49888833 0.69237425
#> [7] 0.27306353 0.67676019 0.78084166 0.48038287 0.89792308 0.08307558
#> [13] 0.78084166 0.30180641 0.05572095 0.76652935 0.57898953 0.14721847
#> [19] 0.79505713 0.95000752 0.90453700 0.96265285 0.98145140 0.92417726
#> [25] 0.61243146 0.74475650 0.85086123 0.72241794 0.39270366 0.96894668
#> [31] 0.55337803 0.91764381 0.59571128 0.28757212 0.91110070 0.18115409
#> [37] 0.63706876 0.95000752 0.34880530 0.83712413 0.87126585 0.57898953
#> [43] 0.55337803 0.02478749 0.72993360 0.21267288 0.39270366 0.18115409
#> [49] 0.30180641 0.33706564 0.48038287 0.45212814 0.76652935 0.43306367
#> [55] 0.65323467 0.82317280 0.75930863 0.30180641 0.51731224 0.39270366
#> [61] 0.83712413 0.55337803 0.38158987 0.10663185 0.24326101 0.25828699
#> [67] 0.43306367 0.60410385 0.53552703 0.21267288 0.86448491 0.53552703
#> [73] 0.45212814 0.42283882 0.88469277 0.97521550 0.88469277 0.62885903
#> [79] 0.34880530 0.14721847 0.82317280 0.67676019 0.75206742 0.93068985
#> [85] 0.80917225 0.52643493 0.50814717 0.94358799 0.73735760 0.93068985
#> [91] 0.87126585 0.65323467 0.85086123 0.64517506 0.34880530 0.61243146
#> [97] 0.98765610 0.47095075 0.79505713 0.99383832 0.12797817 0.69237425
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 79 188 192 13 76 79.1 66 5 133 58 43 86 133.1
#> 16.23 16.16 16.44 14.34 19.22 16.23 22.13 16.43 14.65 19.34 12.10 23.81 14.65
#> 139 78 180 134 69 57 187 107 183 70 52 117 29
#> 21.49 23.88 14.82 17.81 23.23 14.46 9.92 11.18 9.24 7.38 10.42 17.46 15.45
#> 177 100 190 16 40 10 184 136 159 92 106 187.1 99
#> 12.53 16.07 20.81 8.71 18.00 10.53 17.77 21.83 10.55 22.92 16.67 9.92 21.19
#> 123 56 134.1 40.1 24 125 113 190.1 92.1 139.1 153 58.1 166
#> 13.00 12.21 17.81 18.00 23.89 15.65 22.86 20.81 22.92 21.49 21.33 19.34 19.98
#> 180.1 158 85 81 157 139.2 179 190.2 123.1 40.2 90 168 63
#> 14.82 20.14 16.44 14.06 15.10 21.49 18.63 20.81 13.00 18.00 20.94 23.72 22.77
#> 169 158.1 110 88 113.1 37 88.1 166.1 68 49 149 49.1 30
#> 22.41 20.14 17.56 18.37 22.86 12.52 18.37 19.98 20.62 12.19 8.37 12.19 17.43
#> 36 69.1 81.1 5.1 18 93 13.1 8 97 145 39 93.1 56.1
#> 21.19 23.23 14.06 16.43 15.21 10.33 14.34 18.43 19.14 10.07 15.59 10.33 12.21
#> 85.1 177.1 130 36.1 117.1 77 105 57.1 127 164 79.2 119 182
#> 16.44 12.53 16.47 21.19 17.46 7.27 19.75 14.46 3.53 23.60 16.23 24.00 24.00
#> 163 200 162 64 72 27 165 27.1 94 22 2 152 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 28 173 46 119.1 196 48 65 200.1 122 64.1 142 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 143 119.2 28.1 173.1 112.1 112.2 200.2 200.3 119.3 161.1 185 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 67 118 112.3 172 126 160 33 94.1 71 7 28.2 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 17.1 17.2 146 137.1 98 151 200.4 165.1 174 144 120 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 196.1 35 20 46.1 74 74.1 151.1 62 21 138 31.1 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.2 74.2 112.4 143.1 118.1 151.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[11]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01063469 0.57257328 0.19079521
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.0451820850 -0.0009253189 -0.2604948899
#> grade_iii, Cure model
#> 0.8541658539
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 106 16.67 1 49 1 0
#> 63 22.77 1 31 1 0
#> 56 12.21 1 60 0 0
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 188 16.16 1 46 0 1
#> 140 12.68 1 59 1 0
#> 10 10.53 1 34 0 0
#> 58 19.34 1 39 0 0
#> 61 10.12 1 36 0 1
#> 5 16.43 1 51 0 1
#> 184 17.77 1 38 0 0
#> 136 21.83 1 43 0 1
#> 157.1 15.10 1 47 0 0
#> 153 21.33 1 55 1 0
#> 99 21.19 1 38 0 1
#> 183 9.24 1 67 1 0
#> 14 12.89 1 21 0 0
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 159 10.55 1 50 0 1
#> 60 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 77 7.27 1 67 0 1
#> 194 22.40 1 38 0 1
#> 129 23.41 1 53 1 0
#> 29 15.45 1 68 1 0
#> 107 11.18 1 54 1 0
#> 194.1 22.40 1 38 0 1
#> 24 23.89 1 38 0 0
#> 13 14.34 1 54 0 1
#> 117 17.46 1 26 0 1
#> 108 18.29 1 39 0 1
#> 170 19.54 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 199 19.81 1 NA 0 1
#> 157.2 15.10 1 47 0 0
#> 192 16.44 1 31 1 0
#> 128 20.35 1 35 0 1
#> 192.1 16.44 1 31 1 0
#> 154 12.63 1 20 1 0
#> 145 10.07 1 65 1 0
#> 166 19.98 1 48 0 0
#> 153.1 21.33 1 55 1 0
#> 179 18.63 1 42 0 0
#> 169 22.41 1 46 0 0
#> 6 15.64 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 127 3.53 1 62 0 1
#> 168 23.72 1 70 0 0
#> 43.1 12.10 1 61 0 1
#> 4.1 17.64 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 199.1 19.81 1 NA 0 1
#> 52 10.42 1 52 0 1
#> 70 7.38 1 30 1 0
#> 60.1 13.15 1 38 1 0
#> 171 16.57 1 41 0 1
#> 181.1 16.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 189.1 10.51 1 NA 1 0
#> 199.2 19.81 1 NA 0 1
#> 92 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 89 11.44 1 NA 0 0
#> 164 23.60 1 76 0 1
#> 76 19.22 1 54 0 1
#> 57 14.46 1 45 0 1
#> 81 14.06 1 34 0 0
#> 168.1 23.72 1 70 0 0
#> 14.2 12.89 1 21 0 0
#> 105.1 19.75 1 60 0 0
#> 157.3 15.10 1 47 0 0
#> 97 19.14 1 65 0 1
#> 157.4 15.10 1 47 0 0
#> 145.1 10.07 1 65 1 0
#> 4.2 17.64 1 NA 0 1
#> 29.1 15.45 1 68 1 0
#> 23 16.92 1 61 0 0
#> 37 12.52 1 57 1 0
#> 194.2 22.40 1 38 0 1
#> 55 19.34 1 69 0 1
#> 77.1 7.27 1 67 0 1
#> 168.2 23.72 1 70 0 0
#> 139 21.49 1 63 1 0
#> 56.1 12.21 1 60 0 0
#> 89.1 11.44 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 145.2 10.07 1 65 1 0
#> 140.1 12.68 1 59 1 0
#> 10.1 10.53 1 34 0 0
#> 99.1 21.19 1 38 0 1
#> 111 17.45 1 47 0 1
#> 81.1 14.06 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 100 16.07 1 60 0 0
#> 187 9.92 1 39 1 0
#> 157.5 15.10 1 47 0 0
#> 184.1 17.77 1 38 0 0
#> 25 6.32 1 34 1 0
#> 140.2 12.68 1 59 1 0
#> 170.1 19.54 1 43 0 1
#> 61.1 10.12 1 36 0 1
#> 168.3 23.72 1 70 0 0
#> 56.2 12.21 1 60 0 0
#> 153.2 21.33 1 55 1 0
#> 127.1 3.53 1 62 0 1
#> 70.1 7.38 1 30 1 0
#> 20 24.00 0 46 1 0
#> 186 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 191.1 24.00 0 60 0 1
#> 75 24.00 0 21 1 0
#> 64 24.00 0 43 0 0
#> 74 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 103 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 46.1 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 3 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 142.1 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 137 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 71.1 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 84 24.00 0 39 0 1
#> 142.2 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 103.1 24.00 0 56 1 0
#> 54.1 24.00 0 53 1 0
#> 185 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 152 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 191.2 24.00 0 60 0 1
#> 80 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 20.1 24.00 0 46 1 0
#> 53 24.00 0 32 0 1
#> 148.1 24.00 0 61 1 0
#> 178 24.00 0 52 1 0
#> 103.2 24.00 0 56 1 0
#> 87.1 24.00 0 27 0 0
#> 120.1 24.00 0 68 0 1
#> 178.1 24.00 0 52 1 0
#> 141.2 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 152.1 24.00 0 36 0 1
#> 112.1 24.00 0 61 0 0
#> 132 24.00 0 55 0 0
#> 33.1 24.00 0 53 0 0
#> 21.1 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 132.1 24.00 0 55 0 0
#> 141.3 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 22 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 104 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 33.2 24.00 0 53 0 0
#> 12.1 24.00 0 63 0 0
#> 64.1 24.00 0 43 0 0
#> 186.1 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 178.2 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 161 24.00 0 45 0 0
#> 102 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0452 NA NA NA
#> 2 age, Cure model -0.000925 NA NA NA
#> 3 grade_ii, Cure model -0.260 NA NA NA
#> 4 grade_iii, Cure model 0.854 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0106 NA NA NA
#> 2 grade_ii, Survival model 0.573 NA NA NA
#> 3 grade_iii, Survival model 0.191 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.0451821 -0.0009253 -0.2604949 0.8541659
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 251.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.0451820850 -0.0009253189 -0.2604948899 0.8541658539
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01063469 0.57257328 0.19079521
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4591442440 0.3139664236 0.0424084458 0.6840532569 0.7190501987
#> [6] 0.0488687486 0.3957022219 0.6264992687 0.7669222331 0.2087543499
#> [11] 0.8154595468 0.3853599178 0.2646013338 0.0832152195 0.4591442440
#> [16] 0.0984560094 0.1197437270 0.9013813511 0.5922112592 0.3342677572
#> [21] 0.5922112592 0.1578436042 0.1197437270 0.7548640308 0.5693935063
#> [26] 0.3445505349 0.9381537786 0.0628521815 0.0229435104 0.4378273596
#> [31] 0.7428612227 0.0628521815 0.0007829461 0.5349381284 0.2839733241
#> [36] 0.2549704015 0.1913705803 0.4591442440 0.3651117892 0.1498384892
#> [41] 0.3651117892 0.6608882192 0.8399694351 0.1660144391 0.0984560094
#> [46] 0.2454119480 0.0556904128 0.4166547578 0.4166547578 0.9751812110
#> [51] 0.0035018441 0.7190501987 0.1743493254 0.7910777571 0.9137578262
#> [56] 0.5693935063 0.3240825098 0.3445505349 0.1419037904 0.0356685300
#> [61] 0.0292534120 0.0166293964 0.2267055978 0.5235471586 0.5464068905
#> [66] 0.0035018441 0.5922112592 0.1743493254 0.4591442440 0.2359857798
#> [71] 0.4591442440 0.8399694351 0.4378273596 0.3038331212 0.6724674394
#> [76] 0.0628521815 0.2087543499 0.9381537786 0.0035018441 0.0908057656
#> [81] 0.6840532569 0.8766432965 0.8399694351 0.6264992687 0.7669222331
#> [86] 0.1197437270 0.2938586103 0.5464068905 0.7910777571 0.4061147507
#> [91] 0.8890270320 0.4591442440 0.2646013338 0.9628103948 0.6264992687
#> [96] 0.1913705803 0.8154595468 0.0035018441 0.6840532569 0.0984560094
#> [101] 0.9751812110 0.9137578262 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 157 106 63 56 43 15 188 140 10 58 61 5 184
#> 15.10 16.67 22.77 12.21 12.10 22.68 16.16 12.68 10.53 19.34 10.12 16.43 17.77
#> 136 157.1 153 99 183 14 130 14.1 150 36 159 60 181
#> 21.83 15.10 21.33 21.19 9.24 12.89 16.47 12.89 20.33 21.19 10.55 13.15 16.46
#> 77 194 129 29 107 194.1 24 13 117 108 170 157.2 192
#> 7.27 22.40 23.41 15.45 11.18 22.40 23.89 14.34 17.46 18.29 19.54 15.10 16.44
#> 128 192.1 154 145 166 153.1 179 169 6 6.1 127 168 43.1
#> 20.35 16.44 12.63 10.07 19.98 21.33 18.63 22.41 15.64 15.64 3.53 23.72 12.10
#> 105 52 70 60.1 171 181.1 90 92 69 164 76 57 81
#> 19.75 10.42 7.38 13.15 16.57 16.46 20.94 22.92 23.23 23.60 19.22 14.46 14.06
#> 168.1 14.2 105.1 157.3 97 157.4 145.1 29.1 23 37 194.2 55 77.1
#> 23.72 12.89 19.75 15.10 19.14 15.10 10.07 15.45 16.92 12.52 22.40 19.34 7.27
#> 168.2 139 56.1 101 145.2 140.1 10.1 99.1 111 81.1 52.1 100 187
#> 23.72 21.49 12.21 9.97 10.07 12.68 10.53 21.19 17.45 14.06 10.42 16.07 9.92
#> 157.5 184.1 25 140.2 170.1 61.1 168.3 56.2 153.2 127.1 70.1 20 186
#> 15.10 17.77 6.32 12.68 19.54 10.12 23.72 12.21 21.33 3.53 7.38 24.00 24.00
#> 191 191.1 75 64 74 33 7 103 82 47 142 138 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 46.1 162 74.1 54 3 141 87 142.1 38 126 174 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 31 138.1 112 120 146 71.1 11 84 142.2 148 103.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 21 152 141.1 98 191.2 80 83 20.1 53 148.1 178 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 120.1 178.1 141.2 144 152.1 112.1 132 33.1 21.1 163 132.1 141.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 22 12 104 104.1 33.2 12.1 64.1 186.1 131 178.2 160 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 122 48 17 65 161 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[12]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006726794 0.349606355 0.348058369
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.078141109 -0.003348138 0.133953413
#> grade_iii, Cure model
#> 1.589327659
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 91 5.33 1 61 0 1
#> 86 23.81 1 58 0 1
#> 86.1 23.81 1 58 0 1
#> 51 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 4 17.64 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 14 12.89 1 21 0 0
#> 175 21.91 1 43 0 0
#> 111 17.45 1 47 0 1
#> 32 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 81 14.06 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 127 3.53 1 62 0 1
#> 157 15.10 1 47 0 0
#> 164 23.60 1 76 0 1
#> 154.1 12.63 1 20 1 0
#> 77 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 56 12.21 1 60 0 0
#> 70 7.38 1 30 1 0
#> 105 19.75 1 60 0 0
#> 56.1 12.21 1 60 0 0
#> 45 17.42 1 54 0 1
#> 6 15.64 1 39 0 0
#> 43 12.10 1 61 0 1
#> 13 14.34 1 54 0 1
#> 56.2 12.21 1 60 0 0
#> 8 18.43 1 32 0 0
#> 60 13.15 1 38 1 0
#> 101 9.97 1 10 0 1
#> 36 21.19 1 48 0 1
#> 177 12.53 1 75 0 0
#> 197.1 21.60 1 69 1 0
#> 16 8.71 1 71 0 1
#> 4.1 17.64 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 60.1 13.15 1 38 1 0
#> 107 11.18 1 54 1 0
#> 108 18.29 1 39 0 1
#> 166 19.98 1 48 0 0
#> 149 8.37 1 33 1 0
#> 99 21.19 1 38 0 1
#> 43.1 12.10 1 61 0 1
#> 133 14.65 1 57 0 0
#> 23 16.92 1 61 0 0
#> 69 23.23 1 25 0 1
#> 111.1 17.45 1 47 0 1
#> 43.2 12.10 1 61 0 1
#> 29 15.45 1 68 1 0
#> 111.2 17.45 1 47 0 1
#> 190 20.81 1 42 1 0
#> 68 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 108.1 18.29 1 39 0 1
#> 90 20.94 1 50 0 1
#> 170 19.54 1 43 0 1
#> 167 15.55 1 56 1 0
#> 128 20.35 1 35 0 1
#> 105.1 19.75 1 60 0 0
#> 24.1 23.89 1 38 0 0
#> 177.1 12.53 1 75 0 0
#> 140 12.68 1 59 1 0
#> 89 11.44 1 NA 0 0
#> 32.1 20.90 1 37 1 0
#> 41 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 23.1 16.92 1 61 0 0
#> 8.1 18.43 1 32 0 0
#> 52 10.42 1 52 0 1
#> 189.1 10.51 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 10 10.53 1 34 0 0
#> 192 16.44 1 31 1 0
#> 56.3 12.21 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 150 20.33 1 48 0 0
#> 107.1 11.18 1 54 1 0
#> 101.1 9.97 1 10 0 1
#> 187 9.92 1 39 1 0
#> 13.1 14.34 1 54 0 1
#> 177.2 12.53 1 75 0 0
#> 43.3 12.10 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 51.1 18.23 1 83 0 1
#> 85 16.44 1 36 0 0
#> 40 18.00 1 28 1 0
#> 50 10.02 1 NA 1 0
#> 91.2 5.33 1 61 0 1
#> 5 16.43 1 51 0 1
#> 139 21.49 1 63 1 0
#> 107.2 11.18 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 13.2 14.34 1 54 0 1
#> 56.4 12.21 1 60 0 0
#> 117.1 17.46 1 26 0 1
#> 179.1 18.63 1 42 0 0
#> 63.1 22.77 1 31 1 0
#> 70.1 7.38 1 30 1 0
#> 127.1 3.53 1 62 0 1
#> 43.4 12.10 1 61 0 1
#> 127.2 3.53 1 62 0 1
#> 5.1 16.43 1 51 0 1
#> 24.2 23.89 1 38 0 0
#> 21 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 47 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 148 24.00 0 61 1 0
#> 178 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 198 24.00 0 66 0 1
#> 196 24.00 0 19 0 0
#> 87 24.00 0 27 0 0
#> 17 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 73 24.00 0 NA 0 1
#> 46 24.00 0 71 0 0
#> 147.1 24.00 0 76 1 0
#> 182 24.00 0 35 0 0
#> 28 24.00 0 67 1 0
#> 135 24.00 0 58 1 0
#> 102.1 24.00 0 49 0 0
#> 144 24.00 0 28 0 1
#> 142 24.00 0 53 0 0
#> 146.1 24.00 0 63 1 0
#> 142.1 24.00 0 53 0 0
#> 148.1 24.00 0 61 1 0
#> 102.2 24.00 0 49 0 0
#> 186 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 21.1 24.00 0 47 0 0
#> 182.1 24.00 0 35 0 0
#> 115.1 24.00 0 NA 1 0
#> 163 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 148.2 24.00 0 61 1 0
#> 80 24.00 0 41 0 0
#> 115.2 24.00 0 NA 1 0
#> 172.1 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 148.3 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 122 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 200 24.00 0 64 0 0
#> 143.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 198.1 24.00 0 66 0 1
#> 54 24.00 0 53 1 0
#> 38 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 21.2 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 17.1 24.00 0 38 0 1
#> 38.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 82 24.00 0 34 0 0
#> 64 24.00 0 43 0 0
#> 132 24.00 0 55 0 0
#> 46.1 24.00 0 71 0 0
#> 80.1 24.00 0 41 0 0
#> 196.1 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 146.2 24.00 0 63 1 0
#> 28.1 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 148.4 24.00 0 61 1 0
#> 21.3 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 104 24.00 0 50 1 0
#> 80.2 24.00 0 41 0 0
#> 103.1 24.00 0 56 1 0
#> 53 24.00 0 32 0 1
#> 35 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 34 24.00 0 36 0 0
#> 163.1 24.00 0 66 0 0
#> 44.1 24.00 0 56 0 0
#> 98 24.00 0 34 1 0
#> 185.1 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 17.2 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0781 NA NA NA
#> 2 age, Cure model -0.00335 NA NA NA
#> 3 grade_ii, Cure model 0.134 NA NA NA
#> 4 grade_iii, Cure model 1.59 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00673 NA NA NA
#> 2 grade_ii, Survival model 0.350 NA NA NA
#> 3 grade_iii, Survival model 0.348 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.078141 -0.003348 0.133953 1.589328
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 238.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.078141109 -0.003348138 0.133953413 1.589327659
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006726794 0.349606355 0.348058369
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4683145 0.9672876 0.1676623 0.1676623 0.5611644 0.4875787 0.0637868
#> [8] 0.7788518 0.2738423 0.6113525 0.3640958 0.7922109 0.7586501 0.9616419
#> [15] 0.9838001 0.7170485 0.2074443 0.7922109 0.9559700 0.2892565 0.8245832
#> [22] 0.9445776 0.4385814 0.8245832 0.6347981 0.6952997 0.8558459 0.7383272
#> [29] 0.8245832 0.5156761 0.7654701 0.9154792 0.3287274 0.8053148 0.2892565
#> [36] 0.9330206 0.4970816 0.2433226 0.1383773 0.7654701 0.8858645 0.5433495
#> [43] 0.4282932 0.9388128 0.3287274 0.8558459 0.7241841 0.6426106 0.2258638
#> [50] 0.6113525 0.8558459 0.7098863 0.6113525 0.3859262 0.3967270 0.5341110
#> [57] 0.5433495 0.3524302 0.4584584 0.7026334 0.4074276 0.4385814 0.0637868
#> [64] 0.8053148 0.7855628 0.3640958 0.5781824 0.5950263 0.6426106 0.5156761
#> [71] 0.9095700 0.4683145 0.9036218 0.6579525 0.8245832 0.6879427 0.4179100
#> [78] 0.8858645 0.9154792 0.9271819 0.7383272 0.8053148 0.8558459 0.9672876
#> [85] 0.5611644 0.6579525 0.5866474 0.9672876 0.6731139 0.3158079 0.8858645
#> [92] 0.7312870 0.7383272 0.8245832 0.5950263 0.4970816 0.2433226 0.9445776
#> [99] 0.9838001 0.8558459 0.9838001 0.6731139 0.0637868 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 58 91 86 86.1 51 97 24 14 175 111 32 154 81
#> 19.34 5.33 23.81 23.81 18.23 19.14 23.89 12.89 21.91 17.45 20.90 12.63 14.06
#> 25 127 157 164 154.1 77 197 56 70 105 56.1 45 6
#> 6.32 3.53 15.10 23.60 12.63 7.27 21.60 12.21 7.38 19.75 12.21 17.42 15.64
#> 43 13 56.2 8 60 101 36 177 197.1 16 179 63 78
#> 12.10 14.34 12.21 18.43 13.15 9.97 21.19 12.53 21.60 8.71 18.63 22.77 23.88
#> 60.1 107 108 166 149 99 43.1 133 23 69 111.1 43.2 29
#> 13.15 11.18 18.29 19.98 8.37 21.19 12.10 14.65 16.92 23.23 17.45 12.10 15.45
#> 111.2 190 68 88 108.1 90 170 167 128 105.1 24.1 177.1 140
#> 17.45 20.81 20.62 18.37 18.29 20.94 19.54 15.55 20.35 19.75 23.89 12.53 12.68
#> 32.1 41 117 23.1 8.1 52 58.1 10 192 56.3 125 150 107.1
#> 20.90 18.02 17.46 16.92 18.43 10.42 19.34 10.53 16.44 12.21 15.65 20.33 11.18
#> 101.1 187 13.1 177.2 43.3 91.1 51.1 85 40 91.2 5 139 107.2
#> 9.97 9.92 14.34 12.53 12.10 5.33 18.23 16.44 18.00 5.33 16.43 21.49 11.18
#> 57 13.2 56.4 117.1 179.1 63.1 70.1 127.1 43.4 127.2 5.1 24.2 21
#> 14.46 14.34 12.21 17.46 18.63 22.77 7.38 3.53 12.10 3.53 16.43 23.89 24.00
#> 75 47 165 146 120 143 131 102 148 178 20 174 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 87 17 147 46 147.1 182 28 135 102.1 144 142 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 148.1 102.2 186 21.1 182.1 163 172 148.2 80 172.1 44 148.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 122 103 200 143.1 119 198.1 54 38 186.1 121 21.2 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 38.1 185 95 82 64 132 46.1 80.1 196.1 72 146.2 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 148.4 21.3 2 104 80.2 103.1 53 35 200.1 34 163.1 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 185.1 75.1 17.2 87.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[13]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00524814 0.57112537 0.11632400
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.096175921 0.022008623 -0.008782883
#> grade_iii, Cure model
#> 0.790285058
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 99 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 93 10.33 1 52 0 1
#> 37 12.52 1 57 1 0
#> 149 8.37 1 33 1 0
#> 89 11.44 1 NA 0 0
#> 70 7.38 1 30 1 0
#> 4 17.64 1 NA 0 1
#> 29 15.45 1 68 1 0
#> 125 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 110 17.56 1 65 0 1
#> 155 13.08 1 26 0 0
#> 130 16.47 1 53 0 1
#> 69 23.23 1 25 0 1
#> 41 18.02 1 40 1 0
#> 179 18.63 1 42 0 0
#> 133 14.65 1 57 0 0
#> 51 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 177.1 12.53 1 75 0 0
#> 125.1 15.65 1 67 1 0
#> 51.1 18.23 1 83 0 1
#> 97.1 19.14 1 65 0 1
#> 52 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 24 23.89 1 38 0 0
#> 10 10.53 1 34 0 0
#> 164 23.60 1 76 0 1
#> 184 17.77 1 38 0 0
#> 190 20.81 1 42 1 0
#> 18 15.21 1 49 1 0
#> 177.2 12.53 1 75 0 0
#> 134 17.81 1 47 1 0
#> 155.1 13.08 1 26 0 0
#> 188 16.16 1 46 0 1
#> 29.1 15.45 1 68 1 0
#> 6 15.64 1 39 0 0
#> 51.2 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 77 7.27 1 67 0 1
#> 24.1 23.89 1 38 0 0
#> 99.1 21.19 1 38 0 1
#> 8.1 18.43 1 32 0 0
#> 51.3 18.23 1 83 0 1
#> 6.1 15.64 1 39 0 0
#> 63 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 89.1 11.44 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 170 19.54 1 43 0 1
#> 170.1 19.54 1 43 0 1
#> 188.1 16.16 1 46 0 1
#> 13 14.34 1 54 0 1
#> 134.1 17.81 1 47 1 0
#> 16 8.71 1 71 0 1
#> 4.1 17.64 1 NA 0 1
#> 130.1 16.47 1 53 0 1
#> 23.1 16.92 1 61 0 0
#> 49 12.19 1 48 1 0
#> 36 21.19 1 48 0 1
#> 129 23.41 1 53 1 0
#> 108 18.29 1 39 0 1
#> 128 20.35 1 35 0 1
#> 167 15.55 1 56 1 0
#> 24.2 23.89 1 38 0 0
#> 166 19.98 1 48 0 0
#> 168 23.72 1 70 0 0
#> 136.1 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 52.1 10.42 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 68 20.62 1 44 0 0
#> 37.2 12.52 1 57 1 0
#> 6.2 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 78 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 133.1 14.65 1 57 0 0
#> 52.2 10.42 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 111.1 17.45 1 47 0 1
#> 125.2 15.65 1 67 1 0
#> 145 10.07 1 65 1 0
#> 181 16.46 1 45 0 1
#> 97.2 19.14 1 65 0 1
#> 57 14.46 1 45 0 1
#> 136.2 21.83 1 43 0 1
#> 183 9.24 1 67 1 0
#> 154.1 12.63 1 20 1 0
#> 81 14.06 1 34 0 0
#> 85 16.44 1 36 0 0
#> 128.1 20.35 1 35 0 1
#> 56 12.21 1 60 0 0
#> 159 10.55 1 50 0 1
#> 70.1 7.38 1 30 1 0
#> 150 20.33 1 48 0 0
#> 145.1 10.07 1 65 1 0
#> 188.2 16.16 1 46 0 1
#> 85.1 16.44 1 36 0 0
#> 158 20.14 1 74 1 0
#> 155.2 13.08 1 26 0 0
#> 30 17.43 1 78 0 0
#> 123 13.00 1 44 1 0
#> 189 10.51 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 69.1 23.23 1 25 0 1
#> 175 21.91 1 43 0 0
#> 8.2 18.43 1 32 0 0
#> 64 24.00 0 43 0 0
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 11 24.00 0 42 0 1
#> 119 24.00 0 17 0 0
#> 35 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 119.1 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 72 24.00 0 40 0 1
#> 162 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 44.1 24.00 0 56 0 0
#> 20 24.00 0 46 1 0
#> 196 24.00 0 19 0 0
#> 104 24.00 0 50 1 0
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 75.1 24.00 0 21 1 0
#> 147 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 185.1 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 148.1 24.00 0 61 1 0
#> 11.1 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 64.1 24.00 0 43 0 0
#> 102 24.00 0 49 0 0
#> 185.2 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 38 24.00 0 31 1 0
#> 148.2 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 200 24.00 0 64 0 0
#> 176 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 193 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 34 24.00 0 36 0 0
#> 75.2 24.00 0 21 1 0
#> 109 24.00 0 48 0 0
#> 193.1 24.00 0 45 0 1
#> 64.2 24.00 0 43 0 0
#> 27 24.00 0 63 1 0
#> 64.3 24.00 0 43 0 0
#> 137 24.00 0 45 1 0
#> 161.2 24.00 0 45 0 0
#> 120 24.00 0 68 0 1
#> 31 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 119.2 24.00 0 17 0 0
#> 94 24.00 0 51 0 1
#> 144 24.00 0 28 0 1
#> 34.1 24.00 0 36 0 0
#> 131 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 143 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 186.1 24.00 0 45 1 0
#> 148.3 24.00 0 61 1 0
#> 144.1 24.00 0 28 0 1
#> 102.1 24.00 0 49 0 0
#> 35.1 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 47 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 102.2 24.00 0 49 0 0
#> 185.3 24.00 0 44 1 0
#> 104.1 24.00 0 50 1 0
#> 11.2 24.00 0 42 0 1
#> 173.1 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 104.2 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 21.1 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 11.3 24.00 0 42 0 1
#> 152 24.00 0 36 0 1
#> 27.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.10 NA NA NA
#> 2 age, Cure model 0.0220 NA NA NA
#> 3 grade_ii, Cure model -0.00878 NA NA NA
#> 4 grade_iii, Cure model 0.790 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00525 NA NA NA
#> 2 grade_ii, Survival model 0.571 NA NA NA
#> 3 grade_iii, Survival model 0.116 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.096176 0.022009 -0.008783 0.790285
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 255.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.096175921 0.022008623 -0.008782883 0.790285058
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00524814 0.57112537 0.11632400
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.32206932 0.69041664 0.95958746 0.94180548 0.88092104 0.97714369
#> [7] 0.98292498 0.76939341 0.72016666 0.63633668 0.86194090 0.59635662
#> [13] 0.82291385 0.65195565 0.18463013 0.56339748 0.48409968 0.78966758
#> [19] 0.52953966 0.45666379 0.86194090 0.72016666 0.52953966 0.45666379
#> [25] 0.92382422 0.25978145 0.04549267 0.91773438 0.14803500 0.58818471
#> [31] 0.35476983 0.78294007 0.86194090 0.57190484 0.82291385 0.69799236
#> [37] 0.76939341 0.74135205 0.52953966 0.49337933 0.99431040 0.04549267
#> [43] 0.32206932 0.49337933 0.52953966 0.74135205 0.23103914 0.60446411
#> [49] 0.21550839 0.42763302 0.42763302 0.69799236 0.80965036 0.57190484
#> [55] 0.97132435 0.65195565 0.63633668 0.90552007 0.32206932 0.16765911
#> [61] 0.52042457 0.37636406 0.76240087 0.04549267 0.41765898 0.12649421
#> [67] 0.25978145 0.44698489 0.92382422 0.88092104 0.36560834 0.88092104
#> [73] 0.74135205 0.29786501 0.10320831 0.61254043 0.78966758 0.92382422
#> [79] 0.84910374 0.61254043 0.72016666 0.94781946 0.66739575 0.45666379
#> [85] 0.80298650 0.25978145 0.96548295 0.84910374 0.81628737 0.67512298
#> [91] 0.37636406 0.89935026 0.91163664 0.98292498 0.39715864 0.94781946
#> [97] 0.69799236 0.67512298 0.40761625 0.82291385 0.62840477 0.84256484
#> [103] 0.31028846 0.18463013 0.24551662 0.49337933 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 99 79 101 93 37 149 70 29 125 23 177 110 155
#> 21.19 16.23 9.97 10.33 12.52 8.37 7.38 15.45 15.65 16.92 12.53 17.56 13.08
#> 130 69 41 179 133 51 97 177.1 125.1 51.1 97.1 52 136
#> 16.47 23.23 18.02 18.63 14.65 18.23 19.14 12.53 15.65 18.23 19.14 10.42 21.83
#> 24 10 164 184 190 18 177.2 134 155.1 188 29.1 6 51.2
#> 23.89 10.53 23.60 17.77 20.81 15.21 12.53 17.81 13.08 16.16 15.45 15.64 18.23
#> 8 77 24.1 99.1 8.1 51.3 6.1 63 117 92 170 170.1 188.1
#> 18.43 7.27 23.89 21.19 18.43 18.23 15.64 22.77 17.46 22.92 19.54 19.54 16.16
#> 13 134.1 16 130.1 23.1 49 36 129 108 128 167 24.2 166
#> 14.34 17.81 8.71 16.47 16.92 12.19 21.19 23.41 18.29 20.35 15.55 23.89 19.98
#> 168 136.1 76 52.1 37.1 68 37.2 6.2 197 78 111 133.1 52.2
#> 23.72 21.83 19.22 10.42 12.52 20.62 12.52 15.64 21.60 23.88 17.45 14.65 10.42
#> 154 111.1 125.2 145 181 97.2 57 136.2 183 154.1 81 85 128.1
#> 12.63 17.45 15.65 10.07 16.46 19.14 14.46 21.83 9.24 12.63 14.06 16.44 20.35
#> 56 159 70.1 150 145.1 188.2 85.1 158 155.2 30 123 153 69.1
#> 12.21 10.55 7.38 20.33 10.07 16.16 16.44 20.14 13.08 17.43 13.00 21.33 23.23
#> 175 8.2 64 44 75 62 146 161 161.1 11 119 35 116
#> 21.91 18.43 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 21 2 72 162 172 44.1 20 196 104 174 174.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 65 185 147.1 185.1 148 148.1 11.1 163 53 64.1 102 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 38 148.2 82 200 176 28 193 186 1 34 75.2 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 64.2 27 64.3 137 161.2 120 31 83 119.2 94 144 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 173 143 151 186.1 148.3 144.1 102.1 35.1 12 47 143.1 102.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.3 104.1 11.2 173.1 3 104.2 191 21.1 67 11.3 152 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[14]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00172384 0.82616949 0.56794118
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.71199340 0.01438397 0.12186579
#> grade_iii, Cure model
#> 0.81613005
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 70 7.38 1 30 1 0
#> 105 19.75 1 60 0 0
#> 134 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 52 10.42 1 52 0 1
#> 179 18.63 1 42 0 0
#> 134.1 17.81 1 47 1 0
#> 16 8.71 1 71 0 1
#> 155 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 128.1 20.35 1 35 0 1
#> 16.1 8.71 1 71 0 1
#> 113 22.86 1 34 0 0
#> 6 15.64 1 39 0 0
#> 91 5.33 1 61 0 1
#> 90 20.94 1 50 0 1
#> 136 21.83 1 43 0 1
#> 85 16.44 1 36 0 0
#> 183 9.24 1 67 1 0
#> 69 23.23 1 25 0 1
#> 23 16.92 1 61 0 0
#> 37 12.52 1 57 1 0
#> 68 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 106 16.67 1 49 1 0
#> 187 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 190 20.81 1 42 1 0
#> 107 11.18 1 54 1 0
#> 110 17.56 1 65 0 1
#> 24 23.89 1 38 0 0
#> 99 21.19 1 38 0 1
#> 170 19.54 1 43 0 1
#> 157 15.10 1 47 0 0
#> 167 15.55 1 56 1 0
#> 66 22.13 1 53 0 0
#> 189.1 10.51 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 61 10.12 1 36 0 1
#> 43 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 197 21.60 1 69 1 0
#> 50 10.02 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 37.1 12.52 1 57 1 0
#> 127 3.53 1 62 0 1
#> 45 17.42 1 54 0 1
#> 57 14.46 1 45 0 1
#> 29 15.45 1 68 1 0
#> 124 9.73 1 NA 1 0
#> 16.2 8.71 1 71 0 1
#> 179.1 18.63 1 42 0 0
#> 150 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 70.1 7.38 1 30 1 0
#> 155.1 13.08 1 26 0 0
#> 59 10.16 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 8 18.43 1 32 0 0
#> 36.1 21.19 1 48 0 1
#> 59.1 10.16 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 157.1 15.10 1 47 0 0
#> 140 12.68 1 59 1 0
#> 86 23.81 1 58 0 1
#> 167.1 15.55 1 56 1 0
#> 159 10.55 1 50 0 1
#> 25 6.32 1 34 1 0
#> 168 23.72 1 70 0 0
#> 41 18.02 1 40 1 0
#> 157.2 15.10 1 47 0 0
#> 168.1 23.72 1 70 0 0
#> 50.1 10.02 1 NA 1 0
#> 134.2 17.81 1 47 1 0
#> 150.1 20.33 1 48 0 0
#> 66.2 22.13 1 53 0 0
#> 96 14.54 1 33 0 1
#> 150.2 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 78 23.88 1 43 0 0
#> 177 12.53 1 75 0 0
#> 129 23.41 1 53 1 0
#> 171 16.57 1 41 0 1
#> 40 18.00 1 28 1 0
#> 76 19.22 1 54 0 1
#> 194 22.40 1 38 0 1
#> 63 22.77 1 31 1 0
#> 101.2 9.97 1 10 0 1
#> 51 18.23 1 83 0 1
#> 187.1 9.92 1 39 1 0
#> 60 13.15 1 38 1 0
#> 166.1 19.98 1 48 0 0
#> 180 14.82 1 37 0 0
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 66.3 22.13 1 53 0 0
#> 68.1 20.62 1 44 0 0
#> 113.1 22.86 1 34 0 0
#> 61.1 10.12 1 36 0 1
#> 69.1 23.23 1 25 0 1
#> 195 11.76 1 NA 1 0
#> 127.1 3.53 1 62 0 1
#> 16.3 8.71 1 71 0 1
#> 4.1 17.64 1 NA 0 1
#> 50.2 10.02 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 136.1 21.83 1 43 0 1
#> 149 8.37 1 33 1 0
#> 55 19.34 1 69 0 1
#> 134.3 17.81 1 47 1 0
#> 41.1 18.02 1 40 1 0
#> 42 12.43 1 49 0 1
#> 198 24.00 0 66 0 1
#> 84 24.00 0 39 0 1
#> 83 24.00 0 6 0 0
#> 75 24.00 0 21 1 0
#> 135 24.00 0 58 1 0
#> 151 24.00 0 42 0 0
#> 73 24.00 0 NA 0 1
#> 12 24.00 0 63 0 0
#> 196 24.00 0 19 0 0
#> 115 24.00 0 NA 1 0
#> 33 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 109 24.00 0 48 0 0
#> 75.1 24.00 0 21 1 0
#> 148 24.00 0 61 1 0
#> 47 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 75.2 24.00 0 21 1 0
#> 172 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 65 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 142 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 38 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 151.1 24.00 0 42 0 0
#> 75.3 24.00 0 21 1 0
#> 196.1 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 142.1 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 119 24.00 0 17 0 0
#> 72 24.00 0 40 0 1
#> 22.1 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 74.1 24.00 0 43 0 1
#> 34 24.00 0 36 0 0
#> 38.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 71.1 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 126 24.00 0 48 0 0
#> 119.1 24.00 0 17 0 0
#> 44 24.00 0 56 0 0
#> 126.1 24.00 0 48 0 0
#> 200.1 24.00 0 64 0 0
#> 115.1 24.00 0 NA 1 0
#> 122.1 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 38.2 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 115.2 24.00 0 NA 1 0
#> 38.3 24.00 0 31 1 0
#> 73.2 24.00 0 NA 0 1
#> 38.4 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 47.1 24.00 0 38 0 1
#> 142.2 24.00 0 53 0 0
#> 38.5 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 131 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 87 24.00 0 27 0 0
#> 198.1 24.00 0 66 0 1
#> 121 24.00 0 57 1 0
#> 64.1 24.00 0 43 0 0
#> 31 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 73.3 24.00 0 NA 0 1
#> 174 24.00 0 49 1 0
#> 2 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 94.2 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.712 NA NA NA
#> 2 age, Cure model 0.0144 NA NA NA
#> 3 grade_ii, Cure model 0.122 NA NA NA
#> 4 grade_iii, Cure model 0.816 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00172 NA NA NA
#> 2 grade_ii, Survival model 0.826 NA NA NA
#> 3 grade_iii, Survival model 0.568 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71199 0.01438 0.12187 0.81613
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 250.1
#> Residual Deviance: 242.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71199340 0.01438397 0.12186579 0.81613005
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00172384 0.82616949 0.56794118
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.96706746 0.52823843 0.64652408 0.46064451 0.88490180 0.57542474
#> [7] 0.64652408 0.93880661 0.81353888 0.46064451 0.93880661 0.22195812
#> [13] 0.73719709 0.98367989 0.41948219 0.33753302 0.72271575 0.93296205
#> [19] 0.18923467 0.69269455 0.84029024 0.44040510 0.90327049 0.70034438
#> [25] 0.92119460 0.90327049 0.43012882 0.87240675 0.67729506 0.02376164
#> [31] 0.38761847 0.53796610 0.76548669 0.74446868 0.28436496 0.50892383
#> [37] 0.89108833 0.86607009 0.37578629 0.36334851 0.60295456 0.84029024
#> [43] 0.98916858 0.68503534 0.79995549 0.75852654 0.93880661 0.57542474
#> [49] 0.48013538 0.38761847 0.96706746 0.81353888 0.28436496 0.59373557
#> [55] 0.38761847 0.76548669 0.82697381 0.09663535 0.74446868 0.87867479
#> [61] 0.97816162 0.12336597 0.62100783 0.76548669 0.12336597 0.64652408
#> [67] 0.48013538 0.28436496 0.79306930 0.48013538 0.72271575 0.06062249
#> [73] 0.83363569 0.16902559 0.70787204 0.63808597 0.56617304 0.26975088
#> [79] 0.25440204 0.90327049 0.61205015 0.92119460 0.80678832 0.50892383
#> [85] 0.78613083 0.85968858 0.54753794 0.28436496 0.44040510 0.22195812
#> [91] 0.89108833 0.18923467 0.98916858 0.93880661 0.71532881 0.33753302
#> [97] 0.96141292 0.54753794 0.64652408 0.62100783 0.85323612 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000
#>
#> $Time
#> 70 105 134 128 52 179 134.1 16 155 128.1 16.1 113 6
#> 7.38 19.75 17.81 20.35 10.42 18.63 17.81 8.71 13.08 20.35 8.71 22.86 15.64
#> 91 90 136 85 183 69 23 37 68 101 106 187 101.1
#> 5.33 20.94 21.83 16.44 9.24 23.23 16.92 12.52 20.62 9.97 16.67 9.92 9.97
#> 190 107 110 24 99 170 157 167 66 166 61 43 139
#> 20.81 11.18 17.56 23.89 21.19 19.54 15.10 15.55 22.13 19.98 10.12 12.10 21.49
#> 197 108 37.1 127 45 57 29 16.2 179.1 150 36 70.1 155.1
#> 21.60 18.29 12.52 3.53 17.42 14.46 15.45 8.71 18.63 20.33 21.19 7.38 13.08
#> 66.1 8 36.1 157.1 140 86 167.1 159 25 168 41 157.2 168.1
#> 22.13 18.43 21.19 15.10 12.68 23.81 15.55 10.55 6.32 23.72 18.02 15.10 23.72
#> 134.2 150.1 66.2 96 150.2 192 78 177 129 171 40 76 194
#> 17.81 20.33 22.13 14.54 20.33 16.44 23.88 12.53 23.41 16.57 18.00 19.22 22.40
#> 63 101.2 51 187.1 60 166.1 180 49 58 66.3 68.1 113.1 61.1
#> 22.77 9.97 18.23 9.92 13.15 19.98 14.82 12.19 19.34 22.13 20.62 22.86 10.12
#> 69.1 127.1 16.3 181 136.1 149 55 134.3 41.1 42 198 84 83
#> 23.23 3.53 8.71 16.46 21.83 8.37 19.34 17.81 18.02 12.43 24.00 24.00 24.00
#> 75 135 151 12 196 33 64 109 75.1 148 47 138 75.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 122 27 112 65 94 142 98 38 185 151.1 75.3 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 120 120.1 71 142.1 74 54 22 48 152 200 119 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 53 74.1 34 38.1 162 83.1 71.1 126 119.1 44 126.1 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 138.1 38.2 94.1 38.3 38.4 84.1 47.1 142.2 38.5 9 176 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 98.1 87 198.1 121 64.1 31 178 54.1 174 2 161 94.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[15]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01498368 0.17655845 0.12943397
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.2028233712 0.0002317438 0.2938675156
#> grade_iii, Cure model
#> 0.9126570180
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 101 9.97 1 10 0 1
#> 79 16.23 1 54 1 0
#> 167 15.55 1 56 1 0
#> 171 16.57 1 41 0 1
#> 66 22.13 1 53 0 0
#> 113 22.86 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 168 23.72 1 70 0 0
#> 85 16.44 1 36 0 0
#> 93 10.33 1 52 0 1
#> 139 21.49 1 63 1 0
#> 168.1 23.72 1 70 0 0
#> 111 17.45 1 47 0 1
#> 55 19.34 1 69 0 1
#> 10 10.53 1 34 0 0
#> 108 18.29 1 39 0 1
#> 106 16.67 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 93.1 10.33 1 52 0 1
#> 51 18.23 1 83 0 1
#> 51.1 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 59 10.16 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 101.1 9.97 1 10 0 1
#> 60 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 175 21.91 1 43 0 0
#> 81 14.06 1 34 0 0
#> 123 13.00 1 44 1 0
#> 199 19.81 1 NA 0 1
#> 4 17.64 1 NA 0 1
#> 124 9.73 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 107 11.18 1 54 1 0
#> 61 10.12 1 36 0 1
#> 50.1 10.02 1 NA 1 0
#> 101.2 9.97 1 10 0 1
#> 14 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 39 15.59 1 37 0 1
#> 171.1 16.57 1 41 0 1
#> 56 12.21 1 60 0 0
#> 40 18.00 1 28 1 0
#> 30.1 17.43 1 78 0 0
#> 188 16.16 1 46 0 1
#> 108.1 18.29 1 39 0 1
#> 10.1 10.53 1 34 0 0
#> 59.1 10.16 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 30.2 17.43 1 78 0 0
#> 187 9.92 1 39 1 0
#> 124.1 9.73 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 181.1 16.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 68 20.62 1 44 0 0
#> 15 22.68 1 48 0 0
#> 88.1 18.37 1 47 0 0
#> 129 23.41 1 53 1 0
#> 81.1 14.06 1 34 0 0
#> 145 10.07 1 65 1 0
#> 106.1 16.67 1 49 1 0
#> 171.2 16.57 1 41 0 1
#> 90 20.94 1 50 0 1
#> 10.2 10.53 1 34 0 0
#> 171.3 16.57 1 41 0 1
#> 6 15.64 1 39 0 0
#> 99 21.19 1 38 0 1
#> 32 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 69 23.23 1 25 0 1
#> 123.1 13.00 1 44 1 0
#> 25 6.32 1 34 1 0
#> 190.1 20.81 1 42 1 0
#> 70 7.38 1 30 1 0
#> 195 11.76 1 NA 1 0
#> 68.1 20.62 1 44 0 0
#> 70.1 7.38 1 30 1 0
#> 195.1 11.76 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 154 12.63 1 20 1 0
#> 130 16.47 1 53 0 1
#> 63 22.77 1 31 1 0
#> 57 14.46 1 45 0 1
#> 6.1 15.64 1 39 0 0
#> 134 17.81 1 47 1 0
#> 159 10.55 1 50 0 1
#> 91.1 5.33 1 61 0 1
#> 69.1 23.23 1 25 0 1
#> 57.1 14.46 1 45 0 1
#> 129.1 23.41 1 53 1 0
#> 192 16.44 1 31 1 0
#> 29 15.45 1 68 1 0
#> 133 14.65 1 57 0 0
#> 158 20.14 1 74 1 0
#> 153.1 21.33 1 55 1 0
#> 93.2 10.33 1 52 0 1
#> 6.2 15.64 1 39 0 0
#> 194 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 180 14.82 1 37 0 0
#> 81.2 14.06 1 34 0 0
#> 123.2 13.00 1 44 1 0
#> 192.1 16.44 1 31 1 0
#> 194.1 22.40 1 38 0 1
#> 140 12.68 1 59 1 0
#> 23.1 16.92 1 61 0 0
#> 48 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 135 24.00 0 58 1 0
#> 160 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 120 24.00 0 68 0 1
#> 44 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 38 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 48.1 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 2 24.00 0 9 0 0
#> 131 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 2.1 24.00 0 9 0 0
#> 7 24.00 0 37 1 0
#> 120.1 24.00 0 68 0 1
#> 12.1 24.00 0 63 0 0
#> 151 24.00 0 42 0 0
#> 191.1 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 82 24.00 0 34 0 0
#> 83.1 24.00 0 6 0 0
#> 74 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 162.1 24.00 0 51 0 0
#> 83.2 24.00 0 6 0 0
#> 200 24.00 0 64 0 0
#> 47.1 24.00 0 38 0 1
#> 82.1 24.00 0 34 0 0
#> 28 24.00 0 67 1 0
#> 103 24.00 0 56 1 0
#> 138.1 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 118 24.00 0 44 1 0
#> 12.2 24.00 0 63 0 0
#> 144 24.00 0 28 0 1
#> 186 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 72 24.00 0 40 0 1
#> 73 24.00 0 NA 0 1
#> 2.2 24.00 0 9 0 0
#> 185 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 98 24.00 0 34 1 0
#> 156 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 135.1 24.00 0 58 1 0
#> 109 24.00 0 48 0 0
#> 160.1 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 31 24.00 0 36 0 1
#> 87 24.00 0 27 0 0
#> 163 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 21 24.00 0 47 0 0
#> 163.1 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 82.2 24.00 0 34 0 0
#> 173 24.00 0 19 0 1
#> 74.1 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 21.1 24.00 0 47 0 0
#> 135.2 24.00 0 58 1 0
#> 80.1 24.00 0 41 0 0
#> 109.1 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 198.1 24.00 0 66 0 1
#> 118.1 24.00 0 44 1 0
#> 120.2 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 122.1 24.00 0 66 0 0
#> 102.1 24.00 0 49 0 0
#> 80.2 24.00 0 41 0 0
#> 65.1 24.00 0 57 1 0
#> 21.2 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 71.1 24.00 0 51 0 0
#> 131.1 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.203 NA NA NA
#> 2 age, Cure model 0.000232 NA NA NA
#> 3 grade_ii, Cure model 0.294 NA NA NA
#> 4 grade_iii, Cure model 0.913 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0150 NA NA NA
#> 2 grade_ii, Survival model 0.177 NA NA NA
#> 3 grade_iii, Survival model 0.129 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.2028234 0.0002317 0.2938675 0.9126570
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 251.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.2028233712 0.0002317438 0.2938675156 0.9126570180
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01498368 0.17655845 0.12943397
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 8.508109e-01 3.489078e-01 4.315706e-01 2.449675e-01 2.688590e-02
#> [6] 9.737551e-03 9.737551e-03 5.031299e-05 3.163291e-01 7.703246e-01
#> [11] 3.437243e-02 5.031299e-05 1.729222e-01 1.071889e-01 7.240223e-01
#> [16] 1.274850e-01 2.256774e-01 1.007912e-01 7.703246e-01 1.417056e-01
#> [21] 1.417056e-01 1.811530e-01 2.070678e-01 8.508109e-01 5.495481e-01
#> [26] 6.783607e-01 3.052008e-02 5.092075e-01 5.774665e-01 9.660082e-01
#> [31] 6.934270e-01 8.179966e-01 8.508109e-01 6.196476e-01 8.855467e-02
#> [36] 4.192198e-01 2.449675e-01 6.634742e-01 1.569549e-01 1.811530e-01
#> [41] 3.602957e-01 1.274850e-01 7.240223e-01 8.736250e-04 1.811530e-01
#> [46] 8.994018e-01 2.949075e-01 1.138223e-01 8.275785e-02 2.949075e-01
#> [51] 3.847114e-02 7.181158e-02 1.746072e-02 1.138223e-01 2.233879e-03
#> [56] 5.092075e-01 8.343151e-01 2.256774e-01 2.449675e-01 5.173226e-02
#> [61] 7.240223e-01 2.449675e-01 3.836008e-01 4.706134e-02 5.660665e-02
#> [66] 6.161699e-02 5.678754e-03 5.774665e-01 9.491849e-01 6.161699e-02
#> [71] 9.160015e-01 7.181158e-02 9.160015e-01 3.718400e-01 6.487831e-01
#> [76] 2.843241e-01 1.463306e-02 4.827932e-01 3.836008e-01 1.648593e-01
#> [81] 7.086484e-01 9.660082e-01 5.678754e-03 4.827932e-01 2.233879e-03
#> [86] 3.163291e-01 4.440950e-01 4.697055e-01 9.455293e-02 3.847114e-02
#> [91] 7.703246e-01 3.836008e-01 2.054513e-02 5.634515e-01 4.568239e-01
#> [96] 5.092075e-01 5.774665e-01 3.163291e-01 2.054513e-02 6.341305e-01
#> [101] 2.070678e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 101 79 167 171 66 113 113.1 168 85 93 139 168.1 111
#> 9.97 16.23 15.55 16.57 22.13 22.86 22.86 23.72 16.44 10.33 21.49 23.72 17.45
#> 55 10 108 106 170 93.1 51 51.1 30 23 101.1 60 43
#> 19.34 10.53 18.29 16.67 19.54 10.33 18.23 18.23 17.43 16.92 9.97 13.15 12.10
#> 175 81 123 91 107 61 101.2 14 150 39 171.1 56 40
#> 21.91 14.06 13.00 5.33 11.18 10.12 9.97 12.89 20.33 15.59 16.57 12.21 18.00
#> 30.1 188 108.1 10.1 164 30.2 187 181 88 128 181.1 153 68
#> 17.43 16.16 18.29 10.53 23.60 17.43 9.92 16.46 18.37 20.35 16.46 21.33 20.62
#> 15 88.1 129 81.1 145 106.1 171.2 90 10.2 171.3 6 99 32
#> 22.68 18.37 23.41 14.06 10.07 16.67 16.57 20.94 10.53 16.57 15.64 21.19 20.90
#> 190 69 123.1 25 190.1 70 68.1 70.1 100 154 130 63 57
#> 20.81 23.23 13.00 6.32 20.81 7.38 20.62 7.38 16.07 12.63 16.47 22.77 14.46
#> 6.1 134 159 91.1 69.1 57.1 129.1 192 29 133 158 153.1 93.2
#> 15.64 17.81 10.55 5.33 23.23 14.46 23.41 16.44 15.45 14.65 20.14 21.33 10.33
#> 6.2 194 155 180 81.2 123.2 192.1 194.1 140 23.1 48 1 135
#> 15.64 22.40 13.08 14.82 14.06 13.00 16.44 22.40 12.68 16.92 24.00 24.00 24.00
#> 160 191 65 120 44 162 80 143 12 38 137 48.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 131 71 54 102 2.1 7 120.1 12.1 151 191.1 138 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 83.1 74 47 162.1 83.2 200 47.1 82.1 28 103 138.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.2 144 186 198 72 2.2 185 34 98 156 121 135.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 116 31 87 163 165 21 163.1 20 82.2 173 74.1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 135.2 80.1 109.1 146 198.1 118.1 120.2 122 122.1 102.1 80.2 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.2 147 71.1 131.1 152
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[16]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01200887 0.59752006 0.35608570
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.1085617870 -0.0004462566 -0.0873861890
#> grade_iii, Cure model
#> 0.3453248291
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 195 11.76 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 51 18.23 1 83 0 1
#> 106 16.67 1 49 1 0
#> 69 23.23 1 25 0 1
#> 179 18.63 1 42 0 0
#> 130 16.47 1 53 0 1
#> 167 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 77 7.27 1 67 0 1
#> 10 10.53 1 34 0 0
#> 55 19.34 1 69 0 1
#> 192 16.44 1 31 1 0
#> 66 22.13 1 53 0 0
#> 145 10.07 1 65 1 0
#> 171 16.57 1 41 0 1
#> 42 12.43 1 49 0 1
#> 15 22.68 1 48 0 0
#> 16 8.71 1 71 0 1
#> 45 17.42 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 110 17.56 1 65 0 1
#> 168 23.72 1 70 0 0
#> 195.1 11.76 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 49 12.19 1 48 1 0
#> 92 22.92 1 47 0 1
#> 128 20.35 1 35 0 1
#> 81 14.06 1 34 0 0
#> 133 14.65 1 57 0 0
#> 171.1 16.57 1 41 0 1
#> 166 19.98 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 117.1 17.46 1 26 0 1
#> 15.1 22.68 1 48 0 0
#> 134 17.81 1 47 1 0
#> 4.1 17.64 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 42.1 12.43 1 49 0 1
#> 153 21.33 1 55 1 0
#> 41.1 18.02 1 40 1 0
#> 45.1 17.42 1 54 0 1
#> 57 14.46 1 45 0 1
#> 32 20.90 1 37 1 0
#> 77.1 7.27 1 67 0 1
#> 63.2 22.77 1 31 1 0
#> 36 21.19 1 48 0 1
#> 49.1 12.19 1 48 1 0
#> 123 13.00 1 44 1 0
#> 150.1 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 187 9.92 1 39 1 0
#> 107 11.18 1 54 1 0
#> 130.1 16.47 1 53 0 1
#> 171.2 16.57 1 41 0 1
#> 183 9.24 1 67 1 0
#> 179.1 18.63 1 42 0 0
#> 175 21.91 1 43 0 0
#> 100 16.07 1 60 0 0
#> 107.1 11.18 1 54 1 0
#> 29.1 15.45 1 68 1 0
#> 86 23.81 1 58 0 1
#> 78 23.88 1 43 0 0
#> 8 18.43 1 32 0 0
#> 100.1 16.07 1 60 0 0
#> 181 16.46 1 45 0 1
#> 183.1 9.24 1 67 1 0
#> 57.1 14.46 1 45 0 1
#> 69.1 23.23 1 25 0 1
#> 169 22.41 1 46 0 0
#> 99 21.19 1 38 0 1
#> 58 19.34 1 39 0 0
#> 41.2 18.02 1 40 1 0
#> 113 22.86 1 34 0 0
#> 93 10.33 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 15.2 22.68 1 48 0 0
#> 76 19.22 1 54 0 1
#> 10.1 10.53 1 34 0 0
#> 181.1 16.46 1 45 0 1
#> 81.1 14.06 1 34 0 0
#> 101 9.97 1 10 0 1
#> 150.2 20.33 1 48 0 0
#> 10.2 10.53 1 34 0 0
#> 179.2 18.63 1 42 0 0
#> 180 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 99.1 21.19 1 38 0 1
#> 6 15.64 1 39 0 0
#> 157 15.10 1 47 0 0
#> 153.1 21.33 1 55 1 0
#> 133.1 14.65 1 57 0 0
#> 133.2 14.65 1 57 0 0
#> 29.2 15.45 1 68 1 0
#> 154 12.63 1 20 1 0
#> 113.1 22.86 1 34 0 0
#> 88 18.37 1 47 0 0
#> 158 20.14 1 74 1 0
#> 183.2 9.24 1 67 1 0
#> 171.3 16.57 1 41 0 1
#> 192.1 16.44 1 31 1 0
#> 107.2 11.18 1 54 1 0
#> 63.3 22.77 1 31 1 0
#> 189 10.51 1 NA 1 0
#> 168.1 23.72 1 70 0 0
#> 50 10.02 1 NA 1 0
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 120 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 28 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 71 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 98 24.00 0 34 1 0
#> 121 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 118 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 64 24.00 0 43 0 0
#> 104 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 191 24.00 0 60 0 1
#> 83 24.00 0 6 0 0
#> 144 24.00 0 28 0 1
#> 95 24.00 0 68 0 1
#> 104.1 24.00 0 50 1 0
#> 191.1 24.00 0 60 0 1
#> 54 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 19 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 146 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 172.1 24.00 0 41 0 0
#> 72.1 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 160.1 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 67.1 24.00 0 25 0 0
#> 132.1 24.00 0 55 0 0
#> 142 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 146.1 24.00 0 63 1 0
#> 62.1 24.00 0 71 0 0
#> 74.1 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 131 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 131.1 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 64.1 24.00 0 43 0 0
#> 72.2 24.00 0 40 0 1
#> 103.1 24.00 0 56 1 0
#> 121.1 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 67.2 24.00 0 25 0 0
#> 9 24.00 0 31 1 0
#> 132.2 24.00 0 55 0 0
#> 148.1 24.00 0 61 1 0
#> 48 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 144.1 24.00 0 28 0 1
#> 95.1 24.00 0 68 0 1
#> 144.2 24.00 0 28 0 1
#> 178 24.00 0 52 1 0
#> 71.1 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 172.2 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 44 24.00 0 56 0 0
#> 112 24.00 0 61 0 0
#> 71.2 24.00 0 51 0 0
#> 132.3 24.00 0 55 0 0
#> 17.1 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 148.2 24.00 0 61 1 0
#> 46.1 24.00 0 71 0 0
#> 98.1 24.00 0 34 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.109 NA NA NA
#> 2 age, Cure model -0.000446 NA NA NA
#> 3 grade_ii, Cure model -0.0874 NA NA NA
#> 4 grade_iii, Cure model 0.345 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0120 NA NA NA
#> 2 grade_ii, Survival model 0.598 NA NA NA
#> 3 grade_iii, Survival model 0.356 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.1085618 -0.0004463 -0.0873862 0.3453248
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 263.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.1085617870 -0.0004462566 -0.0873861890 0.3453248291
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01200887 0.59752006 0.35608570
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.84166090 0.61271554 0.68793580 0.75896398 0.26105099 0.65138316
#> [7] 0.78771724 0.83645850 0.36152622 0.99237782 0.94779040 0.62095942
#> [13] 0.80986665 0.46523334 0.96449257 0.76495910 0.90850520 0.41479667
#> [19] 0.98849386 0.74680355 0.36152622 0.73429049 0.72790313 0.20992944
#> [25] 0.94356499 0.56963966 0.69500940 0.91757498 0.30435184 0.56041167
#> [31] 0.88985941 0.86610812 0.76495910 0.60435289 0.62095942 0.73429049
#> [37] 0.41479667 0.71485255 0.72139491 0.90850520 0.50154997 0.69500940
#> [43] 0.74680355 0.88043250 0.55100183 0.99237782 0.36152622 0.52237014
#> [49] 0.91757498 0.89923623 0.56963966 0.92644874 0.97270954 0.93085462
#> [55] 0.78771724 0.76495910 0.97678002 0.65138316 0.47761675 0.82059225
#> [61] 0.93085462 0.84166090 0.16843633 0.09274763 0.67329900 0.82059225
#> [67] 0.79890331 0.97678002 0.88043250 0.26105099 0.45254956 0.52237014
#> [73] 0.62095942 0.69500940 0.32457738 0.96032605 0.41479667 0.64382572
#> [79] 0.94779040 0.79890331 0.88985941 0.96860637 0.56963966 0.94779040
#> [85] 0.65138316 0.86122698 0.48978689 0.52237014 0.83117190 0.85633031
#> [91] 0.50154997 0.86610812 0.86610812 0.84166090 0.90388629 0.32457738
#> [97] 0.68064724 0.59589904 0.97678002 0.76495910 0.80986665 0.93085462
#> [103] 0.36152622 0.20992944 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 29 105 51 106 69 179 130 167 63 77 10 55 192
#> 15.45 19.75 18.23 16.67 23.23 18.63 16.47 15.55 22.77 7.27 10.53 19.34 16.44
#> 66 145 171 42 15 16 45 63.1 117 110 168 159 150
#> 22.13 10.07 16.57 12.43 22.68 8.71 17.42 22.77 17.46 17.56 23.72 10.55 20.33
#> 41 49 92 128 81 133 171.1 166 55.1 117.1 15.1 134 184
#> 18.02 12.19 22.92 20.35 14.06 14.65 16.57 19.98 19.34 17.46 22.68 17.81 17.77
#> 42.1 153 41.1 45.1 57 32 77.1 63.2 36 49.1 123 150.1 43
#> 12.43 21.33 18.02 17.42 14.46 20.90 7.27 22.77 21.19 12.19 13.00 20.33 12.10
#> 187 107 130.1 171.2 183 179.1 175 100 107.1 29.1 86 78 8
#> 9.92 11.18 16.47 16.57 9.24 18.63 21.91 16.07 11.18 15.45 23.81 23.88 18.43
#> 100.1 181 183.1 57.1 69.1 169 99 58 41.2 113 93 15.2 76
#> 16.07 16.46 9.24 14.46 23.23 22.41 21.19 19.34 18.02 22.86 10.33 22.68 19.22
#> 10.1 181.1 81.1 101 150.2 10.2 179.2 180 136 99.1 6 157 153.1
#> 10.53 16.46 14.06 9.97 20.33 10.53 18.63 14.82 21.83 21.19 15.64 15.10 21.33
#> 133.1 133.2 29.2 154 113.1 88 158 183.2 171.3 192.1 107.2 63.3 168.1
#> 14.65 14.65 15.45 12.63 22.86 18.37 20.14 9.24 16.57 16.44 11.18 22.77 23.72
#> 132 20 120 185 1 28 3 27 62 160 46 148 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 176 98 121 31 118 138 1.1 64 104 74 191 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 95 104.1 191.1 54 82 19 72 146 67 172.1 72.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 160.1 120.1 67.1 132.1 142 156 146.1 62.1 74.1 193 143 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 17 33 200 131.1 122 64.1 72.2 103.1 121.1 173 67.2 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.2 148.1 48 116 102 144.1 95.1 144.2 178 71.1 163 161 172.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 44 112 71.2 132.3 17.1 141 148.2 46.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[17]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002110481 1.123353304 0.701794062
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.46769421 0.01049453 -0.10489283
#> grade_iii, Cure model
#> 0.59668894
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 170 19.54 1 43 0 1
#> 25 6.32 1 34 1 0
#> 43 12.10 1 61 0 1
#> 134 17.81 1 47 1 0
#> 25.1 6.32 1 34 1 0
#> 76 19.22 1 54 0 1
#> 36 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 97 19.14 1 65 0 1
#> 39 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 66 22.13 1 53 0 0
#> 183 9.24 1 67 1 0
#> 166 19.98 1 48 0 0
#> 166.1 19.98 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 145 10.07 1 65 1 0
#> 58.1 19.34 1 39 0 0
#> 145.1 10.07 1 65 1 0
#> 199 19.81 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 61 10.12 1 36 0 1
#> 57 14.46 1 45 0 1
#> 42 12.43 1 49 0 1
#> 69 23.23 1 25 0 1
#> 179 18.63 1 42 0 0
#> 57.1 14.46 1 45 0 1
#> 179.1 18.63 1 42 0 0
#> 91 5.33 1 61 0 1
#> 180 14.82 1 37 0 0
#> 18 15.21 1 49 1 0
#> 39.1 15.59 1 37 0 1
#> 8 18.43 1 32 0 0
#> 130 16.47 1 53 0 1
#> 37 12.52 1 57 1 0
#> 136 21.83 1 43 0 1
#> 70 7.38 1 30 1 0
#> 69.1 23.23 1 25 0 1
#> 92 22.92 1 47 0 1
#> 78 23.88 1 43 0 0
#> 16 8.71 1 71 0 1
#> 39.2 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 39.3 15.59 1 37 0 1
#> 168 23.72 1 70 0 0
#> 139 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 41 18.02 1 40 1 0
#> 101 9.97 1 10 0 1
#> 25.2 6.32 1 34 1 0
#> 136.1 21.83 1 43 0 1
#> 179.2 18.63 1 42 0 0
#> 4.1 17.64 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 187 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 99 21.19 1 38 0 1
#> 29.1 15.45 1 68 1 0
#> 111 17.45 1 47 0 1
#> 70.1 7.38 1 30 1 0
#> 159 10.55 1 50 0 1
#> 24.1 23.89 1 38 0 0
#> 188 16.16 1 46 0 1
#> 111.1 17.45 1 47 0 1
#> 113 22.86 1 34 0 0
#> 166.2 19.98 1 48 0 0
#> 179.3 18.63 1 42 0 0
#> 13 14.34 1 54 0 1
#> 63 22.77 1 31 1 0
#> 66.1 22.13 1 53 0 0
#> 68.1 20.62 1 44 0 0
#> 111.2 17.45 1 47 0 1
#> 42.1 12.43 1 49 0 1
#> 51 18.23 1 83 0 1
#> 10.1 10.53 1 34 0 0
#> 6 15.64 1 39 0 0
#> 52 10.42 1 52 0 1
#> 93 10.33 1 52 0 1
#> 23.1 16.92 1 61 0 0
#> 70.2 7.38 1 30 1 0
#> 197 21.60 1 69 1 0
#> 16.1 8.71 1 71 0 1
#> 123.1 13.00 1 44 1 0
#> 195 11.76 1 NA 1 0
#> 57.2 14.46 1 45 0 1
#> 76.1 19.22 1 54 0 1
#> 86 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 150 20.33 1 48 0 0
#> 140 12.68 1 59 1 0
#> 183.1 9.24 1 67 1 0
#> 101.2 9.97 1 10 0 1
#> 159.1 10.55 1 50 0 1
#> 167 15.55 1 56 1 0
#> 15 22.68 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 101.3 9.97 1 10 0 1
#> 63.1 22.77 1 31 1 0
#> 188.1 16.16 1 46 0 1
#> 128 20.35 1 35 0 1
#> 36.1 21.19 1 48 0 1
#> 150.1 20.33 1 48 0 0
#> 96.1 14.54 1 33 0 1
#> 56 12.21 1 60 0 0
#> 96.2 14.54 1 33 0 1
#> 179.4 18.63 1 42 0 0
#> 136.2 21.83 1 43 0 1
#> 78.1 23.88 1 43 0 0
#> 33 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 31 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 120 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 2 24.00 0 9 0 0
#> 74 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 72 24.00 0 40 0 1
#> 46 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 7 24.00 0 37 1 0
#> 11.1 24.00 0 42 0 1
#> 173 24.00 0 19 0 1
#> 178 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 17.1 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 191 24.00 0 60 0 1
#> 141 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 53.1 24.00 0 32 0 1
#> 132.1 24.00 0 55 0 0
#> 35 24.00 0 51 0 0
#> 74.2 24.00 0 43 0 1
#> 74.3 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 2.2 24.00 0 9 0 0
#> 112 24.00 0 61 0 0
#> 48.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 144.1 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 126 24.00 0 48 0 0
#> 27.1 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 98 24.00 0 34 1 0
#> 48.2 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 161 24.00 0 45 0 0
#> 112.1 24.00 0 61 0 0
#> 62 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 71 24.00 0 51 0 0
#> 17.2 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 54.1 24.00 0 53 1 0
#> 19.1 24.00 0 57 0 1
#> 9.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 132.2 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 82 24.00 0 34 0 0
#> 151 24.00 0 42 0 0
#> 178.1 24.00 0 52 1 0
#> 98.1 24.00 0 34 1 0
#> 94 24.00 0 51 0 1
#> 67 24.00 0 25 0 0
#> 173.1 24.00 0 19 0 1
#> 103.1 24.00 0 56 1 0
#> 73 24.00 0 NA 0 1
#> 148.1 24.00 0 61 1 0
#> 67.1 24.00 0 25 0 0
#> 74.4 24.00 0 43 0 1
#> 17.3 24.00 0 38 0 1
#> 174.1 24.00 0 49 1 0
#> 31.1 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.468 NA NA NA
#> 2 age, Cure model 0.0105 NA NA NA
#> 3 grade_ii, Cure model -0.105 NA NA NA
#> 4 grade_iii, Cure model 0.597 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00211 NA NA NA
#> 2 grade_ii, Survival model 1.12 NA NA NA
#> 3 grade_iii, Survival model 0.702 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46769 0.01049 -0.10489 0.59669
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 257.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46769421 0.01049453 -0.10489283 0.59668894
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002110481 1.123353304 0.701794062
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.53145321 0.98255190 0.87379923 0.65272868 0.98255190 0.55910437
#> [7] 0.42650381 0.88971697 0.68332601 0.57673733 0.73462601 0.83515319
#> [13] 0.33984465 0.95028282 0.50349268 0.50349268 0.54074131 0.91588361
#> [19] 0.54074131 0.91588361 0.79347167 0.91071000 0.81161461 0.85758465
#> [25] 0.21978411 0.58544597 0.81161461 0.58544597 0.99564215 0.78720955
#> [31] 0.78094338 0.73462601 0.62743331 0.69844969 0.85208076 0.36784493
#> [37] 0.96904714 0.21978411 0.25946619 0.10507538 0.95972659 0.73462601
#> [43] 0.45550122 0.73462601 0.19332624 0.41569530 0.76821618 0.64451915
#> [49] 0.92591597 0.98255190 0.36784493 0.58544597 0.04175189 0.94542613
#> [55] 0.92591597 0.42650381 0.76821618 0.66069808 0.96904714 0.87916925
#> [61] 0.04175189 0.71327338 0.66069808 0.27829105 0.50349268 0.58544597
#> [67] 0.82927655 0.29702217 0.33984465 0.45550122 0.66069808 0.85758465
#> [73] 0.63605675 0.88971697 0.72748909 0.90025539 0.90550158 0.68332601
#> [79] 0.96904714 0.40413143 0.95972659 0.83515319 0.81161461 0.55910437
#> [85] 0.16628611 0.70595035 0.48456254 0.84648769 0.95028282 0.92591597
#> [91] 0.87916925 0.76154295 0.32540044 0.92591597 0.29702217 0.71327338
#> [97] 0.47496285 0.42650381 0.48456254 0.79347167 0.86838614 0.79347167
#> [103] 0.58544597 0.36784493 0.10507538 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 170 25 43 134 25.1 76 36 10 23 97 39 123 66
#> 19.54 6.32 12.10 17.81 6.32 19.22 21.19 10.53 16.92 19.14 15.59 13.00 22.13
#> 183 166 166.1 58 145 58.1 145.1 96 61 57 42 69 179
#> 9.24 19.98 19.98 19.34 10.07 19.34 10.07 14.54 10.12 14.46 12.43 23.23 18.63
#> 57.1 179.1 91 180 18 39.1 8 130 37 136 70 69.1 92
#> 14.46 18.63 5.33 14.82 15.21 15.59 18.43 16.47 12.52 21.83 7.38 23.23 22.92
#> 78 16 39.2 68 39.3 168 139 29 41 101 25.2 136.1 179.2
#> 23.88 8.71 15.59 20.62 15.59 23.72 21.49 15.45 18.02 9.97 6.32 21.83 18.63
#> 24 187 101.1 99 29.1 111 70.1 159 24.1 188 111.1 113 166.2
#> 23.89 9.92 9.97 21.19 15.45 17.45 7.38 10.55 23.89 16.16 17.45 22.86 19.98
#> 179.3 13 63 66.1 68.1 111.2 42.1 51 10.1 6 52 93 23.1
#> 18.63 14.34 22.77 22.13 20.62 17.45 12.43 18.23 10.53 15.64 10.42 10.33 16.92
#> 70.2 197 16.1 123.1 57.2 76.1 86 192 150 140 183.1 101.2 159.1
#> 7.38 21.60 8.71 13.00 14.46 19.22 23.81 16.44 20.33 12.68 9.24 9.97 10.55
#> 167 15 101.3 63.1 188.1 128 36.1 150.1 96.1 56 96.2 179.4 136.2
#> 15.55 22.68 9.97 22.77 16.16 20.35 21.19 20.33 14.54 12.21 14.54 18.63 21.83
#> 78.1 33 132 31 172 19 9 148 120 109 48 33.1 11
#> 23.88 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 74 27 17 22 144 72 46 2.1 7 11.1 173 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 74.1 53 17.1 64 191 141 172.1 53.1 132.1 35 74.2 74.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 146 2.2 112 48.1 65 135 144.1 138 83 126 27.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 48.2 80 47 142 54 161 112.1 62 12 174 71 17.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 54.1 19.1 9.1 185 132.2 75 34 82 151 178.1 98.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 173.1 103.1 148.1 67.1 74.4 17.3 174.1 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[18]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0005622517 0.3660698796 -0.1021215342
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.361082990 -0.000391036 0.072187123
#> grade_iii, Cure model
#> 1.456146228
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 127 3.53 1 62 0 1
#> 107 11.18 1 54 1 0
#> 30 17.43 1 78 0 0
#> 45 17.42 1 54 0 1
#> 61 10.12 1 36 0 1
#> 70 7.38 1 30 1 0
#> 15 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 29 15.45 1 68 1 0
#> 97 19.14 1 65 0 1
#> 90 20.94 1 50 0 1
#> 57 14.46 1 45 0 1
#> 153.1 21.33 1 55 1 0
#> 52 10.42 1 52 0 1
#> 92 22.92 1 47 0 1
#> 41 18.02 1 40 1 0
#> 169 22.41 1 46 0 0
#> 183 9.24 1 67 1 0
#> 194 22.40 1 38 0 1
#> 14 12.89 1 21 0 0
#> 145 10.07 1 65 1 0
#> 180 14.82 1 37 0 0
#> 99 21.19 1 38 0 1
#> 69.1 23.23 1 25 0 1
#> 110 17.56 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 14.1 12.89 1 21 0 0
#> 124 9.73 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 10 10.53 1 34 0 0
#> 166 19.98 1 48 0 0
#> 108 18.29 1 39 0 1
#> 189 10.51 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 99.1 21.19 1 38 0 1
#> 117 17.46 1 26 0 1
#> 91 5.33 1 61 0 1
#> 55 19.34 1 69 0 1
#> 92.1 22.92 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 4.1 17.64 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 117.1 17.46 1 26 0 1
#> 18 15.21 1 49 1 0
#> 91.1 5.33 1 61 0 1
#> 149 8.37 1 33 1 0
#> 42 12.43 1 49 0 1
#> 97.1 19.14 1 65 0 1
#> 41.1 18.02 1 40 1 0
#> 140 12.68 1 59 1 0
#> 69.2 23.23 1 25 0 1
#> 159 10.55 1 50 0 1
#> 113 22.86 1 34 0 0
#> 100 16.07 1 60 0 0
#> 68 20.62 1 44 0 0
#> 8 18.43 1 32 0 0
#> 111 17.45 1 47 0 1
#> 23 16.92 1 61 0 0
#> 32 20.90 1 37 1 0
#> 45.1 17.42 1 54 0 1
#> 124.1 9.73 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 89.1 11.44 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 5 16.43 1 51 0 1
#> 85 16.44 1 36 0 0
#> 70.1 7.38 1 30 1 0
#> 56 12.21 1 60 0 0
#> 170 19.54 1 43 0 1
#> 175 21.91 1 43 0 0
#> 86 23.81 1 58 0 1
#> 16 8.71 1 71 0 1
#> 76 19.22 1 54 0 1
#> 133 14.65 1 57 0 0
#> 79 16.23 1 54 1 0
#> 4.2 17.64 1 NA 0 1
#> 30.1 17.43 1 78 0 0
#> 171 16.57 1 41 0 1
#> 127.1 3.53 1 62 0 1
#> 190 20.81 1 42 1 0
#> 42.1 12.43 1 49 0 1
#> 124.2 9.73 1 NA 1 0
#> 89.2 11.44 1 NA 0 0
#> 164 23.60 1 76 0 1
#> 61.1 10.12 1 36 0 1
#> 30.2 17.43 1 78 0 0
#> 113.1 22.86 1 34 0 0
#> 4.3 17.64 1 NA 0 1
#> 55.1 19.34 1 69 0 1
#> 81 14.06 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 57.1 14.46 1 45 0 1
#> 4.4 17.64 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 108.1 18.29 1 39 0 1
#> 110.1 17.56 1 65 0 1
#> 190.1 20.81 1 42 1 0
#> 32.1 20.90 1 37 1 0
#> 164.1 23.60 1 76 0 1
#> 89.3 11.44 1 NA 0 0
#> 168 23.72 1 70 0 0
#> 150.1 20.33 1 48 0 0
#> 101 9.97 1 10 0 1
#> 58 19.34 1 39 0 0
#> 114.1 13.68 1 NA 0 0
#> 199.1 19.81 1 NA 0 1
#> 153.2 21.33 1 55 1 0
#> 37 12.52 1 57 1 0
#> 183.1 9.24 1 67 1 0
#> 71 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 144 24.00 0 28 0 1
#> 115 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 53 24.00 0 32 0 1
#> 148 24.00 0 61 1 0
#> 122 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 3 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 162 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 121 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 103.1 24.00 0 56 1 0
#> 120 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 132 24.00 0 55 0 0
#> 62 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 12 24.00 0 63 0 0
#> 144.1 24.00 0 28 0 1
#> 84 24.00 0 39 0 1
#> 198 24.00 0 66 0 1
#> 165 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 103.2 24.00 0 56 1 0
#> 185 24.00 0 44 1 0
#> 126.1 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 198.1 24.00 0 66 0 1
#> 109 24.00 0 48 0 0
#> 3.1 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 151 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 165.1 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 7.1 24.00 0 37 1 0
#> 71.1 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 151.1 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 64.1 24.00 0 43 0 0
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 82.1 24.00 0 34 0 0
#> 174.1 24.00 0 49 1 0
#> 146 24.00 0 63 1 0
#> 35.1 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 193 24.00 0 45 0 1
#> 48 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 20.1 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 138.1 24.00 0 44 1 0
#> 160.1 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 138.2 24.00 0 44 1 0
#> 3.2 24.00 0 31 1 0
#> 20.2 24.00 0 46 1 0
#> 109.1 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 162.1 24.00 0 51 0 0
#> 146.1 24.00 0 63 1 0
#> 28.2 24.00 0 67 1 0
#> 103.3 24.00 0 56 1 0
#> 191.1 24.00 0 60 0 1
#> 200.1 24.00 0 64 0 0
#> 53.1 24.00 0 32 0 1
#> 35.2 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.361 NA NA NA
#> 2 age, Cure model -0.000391 NA NA NA
#> 3 grade_ii, Cure model 0.0722 NA NA NA
#> 4 grade_iii, Cure model 1.46 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000562 NA NA NA
#> 2 grade_ii, Survival model 0.366 NA NA NA
#> 3 grade_iii, Survival model -0.102 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.361083 -0.000391 0.072187 1.456146
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 252
#> Residual Deviance: 233.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.361082990 -0.000391036 0.072187123 1.456146228
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0005622517 0.3660698796 -0.1021215342
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.049909249 0.980019902 0.797627697 0.518055107 0.549134110 0.848706481
#> [7] 0.930141181 0.138400484 0.185388684 0.653663090 0.392917183 0.248017043
#> [13] 0.694956443 0.185388684 0.838448879 0.080740243 0.445359068 0.150075179
#> [19] 0.889641474 0.161773558 0.725850512 0.869154313 0.674336480 0.216432478
#> [25] 0.049909249 0.465963912 0.725850512 0.310707791 0.818089642 0.331098309
#> [31] 0.424356084 0.950102126 0.216432478 0.486687543 0.960091825 0.351867631
#> [37] 0.080740243 0.818089642 0.126752518 0.486687543 0.664032195 0.960091825
#> [43] 0.920015278 0.766943790 0.392917183 0.445359068 0.746409388 0.049909249
#> [49] 0.807850758 0.103687596 0.643229780 0.300358177 0.413783262 0.507508983
#> [55] 0.570153415 0.259086805 0.549134110 0.591406310 0.591406310 0.622305392
#> [61] 0.591406310 0.930141181 0.787352100 0.341464224 0.173571376 0.005260449
#> [67] 0.909842852 0.382415153 0.684644012 0.632802085 0.518055107 0.580768422
#> [73] 0.980019902 0.280032453 0.766943790 0.028482782 0.848706481 0.518055107
#> [79] 0.103687596 0.351867631 0.715500722 0.694956443 0.216432478 0.424356084
#> [85] 0.465963912 0.280032453 0.259086805 0.028482782 0.016517932 0.310707791
#> [91] 0.879391799 0.351867631 0.185388684 0.756704210 0.889641474 0.000000000
#> [97] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000
#>
#> $Time
#> 69 127 107 30 45 61 70 15 153 29 97 90 57
#> 23.23 3.53 11.18 17.43 17.42 10.12 7.38 22.68 21.33 15.45 19.14 20.94 14.46
#> 153.1 52 92 41 169 183 194 14 145 180 99 69.1 110
#> 21.33 10.42 22.92 18.02 22.41 9.24 22.40 12.89 10.07 14.82 21.19 23.23 17.56
#> 14.1 150 10 166 108 25 99.1 117 91 55 92.1 10.1 63
#> 12.89 20.33 10.53 19.98 18.29 6.32 21.19 17.46 5.33 19.34 22.92 10.53 22.77
#> 117.1 18 91.1 149 42 97.1 41.1 140 69.2 159 113 100 68
#> 17.46 15.21 5.33 8.37 12.43 19.14 18.02 12.68 23.23 10.55 22.86 16.07 20.62
#> 8 111 23 32 45.1 192 192.1 5 85 70.1 56 170 175
#> 18.43 17.45 16.92 20.90 17.42 16.44 16.44 16.43 16.44 7.38 12.21 19.54 21.91
#> 86 16 76 133 79 30.1 171 127.1 190 42.1 164 61.1 30.2
#> 23.81 8.71 19.22 14.65 16.23 17.43 16.57 3.53 20.81 12.43 23.60 10.12 17.43
#> 113.1 55.1 81 57.1 36 108.1 110.1 190.1 32.1 164.1 168 150.1 101
#> 22.86 19.34 14.06 14.46 21.19 18.29 17.56 20.81 20.90 23.60 23.72 20.33 9.97
#> 58 153.2 37 183.1 71 35 28 144 103 53 148 122 102
#> 19.34 21.33 12.52 9.24 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 67 3 160 174 162 82 121 118 138 64 33 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 120 7 196 132 62 33.1 28.1 12 144.1 84 198 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 9 103.2 185 126.1 182 198.1 109 3.1 44 151 87 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 17 147 7.1 71.1 87.1 151.1 11 80 116 64.1 20 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 174.1 146 35.1 21 193 48 72 20.1 27 138.1 160.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.2 3.2 20.2 109.1 98 162.1 146.1 28.2 103.3 191.1 200.1 53.1 35.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[19]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01042215 0.49538144 0.35944266
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.620211532 0.003627298 0.491335143
#> grade_iii, Cure model
#> 1.581156629
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 40 18.00 1 28 1 0
#> 157 15.10 1 47 0 0
#> 171 16.57 1 41 0 1
#> 61 10.12 1 36 0 1
#> 8 18.43 1 32 0 0
#> 125 15.65 1 67 1 0
#> 32 20.90 1 37 1 0
#> 81 14.06 1 34 0 0
#> 92 22.92 1 47 0 1
#> 29 15.45 1 68 1 0
#> 5 16.43 1 51 0 1
#> 43 12.10 1 61 0 1
#> 25 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 41 18.02 1 40 1 0
#> 195 11.76 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 86 23.81 1 58 0 1
#> 164 23.60 1 76 0 1
#> 14 12.89 1 21 0 0
#> 181 16.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 29.1 15.45 1 68 1 0
#> 37 12.52 1 57 1 0
#> 192 16.44 1 31 1 0
#> 179 18.63 1 42 0 0
#> 127 3.53 1 62 0 1
#> 168 23.72 1 70 0 0
#> 128 20.35 1 35 0 1
#> 159 10.55 1 50 0 1
#> 42 12.43 1 49 0 1
#> 168.1 23.72 1 70 0 0
#> 16 8.71 1 71 0 1
#> 124 9.73 1 NA 1 0
#> 157.1 15.10 1 47 0 0
#> 133 14.65 1 57 0 0
#> 171.1 16.57 1 41 0 1
#> 78 23.88 1 43 0 0
#> 195.1 11.76 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 133.1 14.65 1 57 0 0
#> 85 16.44 1 36 0 0
#> 190 20.81 1 42 1 0
#> 43.1 12.10 1 61 0 1
#> 10 10.53 1 34 0 0
#> 124.1 9.73 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 175 21.91 1 43 0 0
#> 40.1 18.00 1 28 1 0
#> 99 21.19 1 38 0 1
#> 39 15.59 1 37 0 1
#> 99.1 21.19 1 38 0 1
#> 128.1 20.35 1 35 0 1
#> 4 17.64 1 NA 0 1
#> 5.1 16.43 1 51 0 1
#> 192.1 16.44 1 31 1 0
#> 129 23.41 1 53 1 0
#> 167 15.55 1 56 1 0
#> 50 10.02 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 157.2 15.10 1 47 0 0
#> 42.1 12.43 1 49 0 1
#> 37.1 12.52 1 57 1 0
#> 13 14.34 1 54 0 1
#> 91 5.33 1 61 0 1
#> 66 22.13 1 53 0 0
#> 188 16.16 1 46 0 1
#> 194 22.40 1 38 0 1
#> 70 7.38 1 30 1 0
#> 14.1 12.89 1 21 0 0
#> 70.1 7.38 1 30 1 0
#> 117.1 17.46 1 26 0 1
#> 61.1 10.12 1 36 0 1
#> 169 22.41 1 46 0 0
#> 145 10.07 1 65 1 0
#> 81.1 14.06 1 34 0 0
#> 49 12.19 1 48 1 0
#> 86.1 23.81 1 58 0 1
#> 188.1 16.16 1 46 0 1
#> 100 16.07 1 60 0 0
#> 130 16.47 1 53 0 1
#> 123 13.00 1 44 1 0
#> 105 19.75 1 60 0 0
#> 26 15.77 1 49 0 1
#> 107 11.18 1 54 1 0
#> 85.1 16.44 1 36 0 0
#> 96 14.54 1 33 0 1
#> 164.1 23.60 1 76 0 1
#> 197 21.60 1 69 1 0
#> 68 20.62 1 44 0 0
#> 16.1 8.71 1 71 0 1
#> 97 19.14 1 65 0 1
#> 149 8.37 1 33 1 0
#> 76 19.22 1 54 0 1
#> 40.2 18.00 1 28 1 0
#> 130.1 16.47 1 53 0 1
#> 43.2 12.10 1 61 0 1
#> 13.1 14.34 1 54 0 1
#> 5.2 16.43 1 51 0 1
#> 52 10.42 1 52 0 1
#> 5.3 16.43 1 51 0 1
#> 79 16.23 1 54 1 0
#> 63 22.77 1 31 1 0
#> 159.1 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 52.1 10.42 1 52 0 1
#> 197.1 21.60 1 69 1 0
#> 159.2 10.55 1 50 0 1
#> 107.1 11.18 1 54 1 0
#> 5.4 16.43 1 51 0 1
#> 155 13.08 1 26 0 0
#> 113 22.86 1 34 0 0
#> 11 24.00 0 42 0 1
#> 172 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 38 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 156 24.00 0 50 1 0
#> 156.1 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 122 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 138 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 11.1 24.00 0 42 0 1
#> 83.1 24.00 0 6 0 0
#> 7 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 163 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 87 24.00 0 27 0 0
#> 98 24.00 0 34 1 0
#> 186.1 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 141 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 156.2 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 173.1 24.00 0 19 0 1
#> 95 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 193 24.00 0 45 0 1
#> 74 24.00 0 43 0 1
#> 98.1 24.00 0 34 1 0
#> 74.1 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 135 24.00 0 58 1 0
#> 104 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 132 24.00 0 55 0 0
#> 62.1 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 9.1 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 186.2 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 83.2 24.00 0 6 0 0
#> 102 24.00 0 49 0 0
#> 104.1 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 109 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 104.2 24.00 0 50 1 0
#> 3.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 94.1 24.00 0 51 0 1
#> 196 24.00 0 19 0 0
#> 87.1 24.00 0 27 0 0
#> 21 24.00 0 47 0 0
#> 165.1 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 12.1 24.00 0 63 0 0
#> 64.1 24.00 0 43 0 0
#> 71 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 196.1 24.00 0 19 0 0
#> 109.1 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 94.2 24.00 0 51 0 1
#> 62.2 24.00 0 71 0 0
#> 21.1 24.00 0 47 0 0
#> 12.2 24.00 0 63 0 0
#> 141.1 24.00 0 44 1 0
#> 102.1 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.620 NA NA NA
#> 2 age, Cure model 0.00363 NA NA NA
#> 3 grade_ii, Cure model 0.491 NA NA NA
#> 4 grade_iii, Cure model 1.58 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0104 NA NA NA
#> 2 grade_ii, Survival model 0.495 NA NA NA
#> 3 grade_iii, Survival model 0.359 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.620212 0.003627 0.491335 1.581157
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 244.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.620211532 0.003627298 0.491335143 1.581156629
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01042215 0.49538144 0.35944266
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.249212366 0.542413494 0.304246587 0.879511063 0.229906572 0.482855815
#> [7] 0.139713362 0.624128274 0.042821289 0.512601829 0.387844406 0.750707654
#> [13] 0.967045086 0.868570401 0.239575320 0.532411773 0.004883058 0.022745871
#> [19] 0.666173205 0.341510456 0.114941714 0.512601829 0.697855350 0.351033149
#> [25] 0.220351821 0.988984793 0.012099337 0.166042636 0.803926570 0.718913142
#> [31] 0.012099337 0.912230157 0.542413494 0.572501815 0.304246587 0.001020563
#> [37] 0.192425952 0.572501815 0.351033149 0.148449564 0.750707654 0.835999484
#> [43] 0.276340324 0.089502214 0.249212366 0.114941714 0.492762202 0.114941714
#> [49] 0.166042636 0.387844406 0.351033149 0.035595268 0.502673744 0.285783263
#> [55] 0.542413494 0.718913142 0.697855350 0.603436433 0.978000086 0.081249237
#> [61] 0.443863021 0.073337714 0.945221960 0.666173205 0.945221960 0.285783263
#> [67] 0.879511063 0.065457536 0.901264726 0.624128274 0.740057906 0.004883058
#> [73] 0.443863021 0.463146246 0.322784048 0.655603242 0.183352427 0.472986618
#> [79] 0.782528276 0.351033149 0.593066305 0.022745871 0.098039912 0.157155518
#> [85] 0.912230157 0.210941759 0.934195355 0.201644719 0.249212366 0.322784048
#> [91] 0.750707654 0.603436433 0.387844406 0.846872195 0.387844406 0.434162593
#> [97] 0.057923444 0.803926570 0.687276056 0.846872195 0.098039912 0.803926570
#> [103] 0.782528276 0.387844406 0.645026890 0.050202256 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 40 157 171 61 8 125 32 81 92 29 5 43 25
#> 18.00 15.10 16.57 10.12 18.43 15.65 20.90 14.06 22.92 15.45 16.43 12.10 6.32
#> 93 41 18 86 164 14 181 36 29.1 37 192 179 127
#> 10.33 18.02 15.21 23.81 23.60 12.89 16.46 21.19 15.45 12.52 16.44 18.63 3.53
#> 168 128 159 42 168.1 16 157.1 133 171.1 78 58 133.1 85
#> 23.72 20.35 10.55 12.43 23.72 8.71 15.10 14.65 16.57 23.88 19.34 14.65 16.44
#> 190 43.1 10 110 175 40.1 99 39 99.1 128.1 5.1 192.1 129
#> 20.81 12.10 10.53 17.56 21.91 18.00 21.19 15.59 21.19 20.35 16.43 16.44 23.41
#> 167 117 157.2 42.1 37.1 13 91 66 188 194 70 14.1 70.1
#> 15.55 17.46 15.10 12.43 12.52 14.34 5.33 22.13 16.16 22.40 7.38 12.89 7.38
#> 117.1 61.1 169 145 81.1 49 86.1 188.1 100 130 123 105 26
#> 17.46 10.12 22.41 10.07 14.06 12.19 23.81 16.16 16.07 16.47 13.00 19.75 15.77
#> 107 85.1 96 164.1 197 68 16.1 97 149 76 40.2 130.1 43.2
#> 11.18 16.44 14.54 23.60 21.60 20.62 8.71 19.14 8.37 19.22 18.00 16.47 12.10
#> 13.1 5.2 52 5.3 79 63 159.1 154 52.1 197.1 159.2 107.1 5.4
#> 14.34 16.43 10.42 16.43 16.23 22.77 10.55 12.63 10.42 21.60 10.55 11.18 16.43
#> 155 113 11 172 173 38 64 156 156.1 160 83 122 137
#> 13.08 22.86 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 62 186 138 75 19 11.1 83.1 7 163 3 87 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 151 141 9 156.2 33 112 173.1 95 34 193 74 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 12 135 104 131 178 65 198 132 62.1 33.1 9.1 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 186.2 72 83.2 102 104.1 27 109 35 126 200 104.2 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 120 148 94.1 196 87.1 21 165.1 17 12.1 64.1 71 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 196.1 109.1 34.1 94.2 62.2 21.1 12.2 141.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[20]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01164842 0.29377687 0.30421117
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.07573894 0.01890611 0.19651332
#> grade_iii, Cure model
#> 1.22092007
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 92 22.92 1 47 0 1
#> 129 23.41 1 53 1 0
#> 124 9.73 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 190 20.81 1 42 1 0
#> 26 15.77 1 49 0 1
#> 155 13.08 1 26 0 0
#> 57 14.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 168 23.72 1 70 0 0
#> 55 19.34 1 69 0 1
#> 190.1 20.81 1 42 1 0
#> 106 16.67 1 49 1 0
#> 97 19.14 1 65 0 1
#> 51 18.23 1 83 0 1
#> 79 16.23 1 54 1 0
#> 5 16.43 1 51 0 1
#> 18 15.21 1 49 1 0
#> 157 15.10 1 47 0 0
#> 180 14.82 1 37 0 0
#> 96 14.54 1 33 0 1
#> 179 18.63 1 42 0 0
#> 99 21.19 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 91 5.33 1 61 0 1
#> 194 22.40 1 38 0 1
#> 55.1 19.34 1 69 0 1
#> 184 17.77 1 38 0 0
#> 39.1 15.59 1 37 0 1
#> 18.1 15.21 1 49 1 0
#> 57.1 14.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 140 12.68 1 59 1 0
#> 88 18.37 1 47 0 0
#> 66 22.13 1 53 0 0
#> 97.1 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 40 18.00 1 28 1 0
#> 177 12.53 1 75 0 0
#> 155.1 13.08 1 26 0 0
#> 197.1 21.60 1 69 1 0
#> 43 12.10 1 61 0 1
#> 168.1 23.72 1 70 0 0
#> 26.1 15.77 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 14 12.89 1 21 0 0
#> 136 21.83 1 43 0 1
#> 88.1 18.37 1 47 0 0
#> 49 12.19 1 48 1 0
#> 90 20.94 1 50 0 1
#> 129.1 23.41 1 53 1 0
#> 16 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 114 13.68 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 16.1 8.71 1 71 0 1
#> 50 10.02 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 164 23.60 1 76 0 1
#> 133 14.65 1 57 0 0
#> 49.2 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 149 8.37 1 33 1 0
#> 40.1 18.00 1 28 1 0
#> 129.2 23.41 1 53 1 0
#> 4.1 17.64 1 NA 0 1
#> 180.1 14.82 1 37 0 0
#> 41 18.02 1 40 1 0
#> 57.2 14.46 1 45 0 1
#> 133.1 14.65 1 57 0 0
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 183 9.24 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 190.2 20.81 1 42 1 0
#> 184.1 17.77 1 38 0 0
#> 190.3 20.81 1 42 1 0
#> 40.2 18.00 1 28 1 0
#> 157.1 15.10 1 47 0 0
#> 170 19.54 1 43 0 1
#> 29 15.45 1 68 1 0
#> 97.2 19.14 1 65 0 1
#> 56.1 12.21 1 60 0 0
#> 92.1 22.92 1 47 0 1
#> 194.1 22.40 1 38 0 1
#> 171 16.57 1 41 0 1
#> 6 15.64 1 39 0 0
#> 43.1 12.10 1 61 0 1
#> 57.3 14.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 96.1 14.54 1 33 0 1
#> 187 9.92 1 39 1 0
#> 192.1 16.44 1 31 1 0
#> 68 20.62 1 44 0 0
#> 158 20.14 1 74 1 0
#> 187.1 9.92 1 39 1 0
#> 149.1 8.37 1 33 1 0
#> 59 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 149.2 8.37 1 33 1 0
#> 150 20.33 1 48 0 0
#> 59.1 10.16 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 14.1 12.89 1 21 0 0
#> 175 21.91 1 43 0 0
#> 192.2 16.44 1 31 1 0
#> 125 15.65 1 67 1 0
#> 169 22.41 1 46 0 0
#> 14.2 12.89 1 21 0 0
#> 24.1 23.89 1 38 0 0
#> 159 10.55 1 50 0 1
#> 34 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 178 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 109.1 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 31 24.00 0 36 0 1
#> 144 24.00 0 28 0 1
#> 71 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 53 24.00 0 32 0 1
#> 142.1 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 156.1 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 103 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 27 24.00 0 63 1 0
#> 75 24.00 0 21 1 0
#> 21 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 156.2 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 71.1 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 87.1 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 109.2 24.00 0 48 0 0
#> 126 24.00 0 48 0 0
#> 17 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 174 24.00 0 49 1 0
#> 7 24.00 0 37 1 0
#> 54 24.00 0 53 1 0
#> 186 24.00 0 45 1 0
#> 146 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 7.1 24.00 0 37 1 0
#> 102 24.00 0 49 0 0
#> 64 24.00 0 43 0 0
#> 174.1 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 71.2 24.00 0 51 0 0
#> 21.1 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 172.1 24.00 0 41 0 0
#> 83.1 24.00 0 6 0 0
#> 141 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 109.3 24.00 0 48 0 0
#> 17.1 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 74 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 172.2 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 74.1 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 196 24.00 0 19 0 0
#> 87.2 24.00 0 27 0 0
#> 27.1 24.00 0 63 1 0
#> 67.1 24.00 0 25 0 0
#> 132.1 24.00 0 55 0 0
#> 83.2 24.00 0 6 0 0
#> 156.3 24.00 0 50 1 0
#> 141.1 24.00 0 44 1 0
#> 178.2 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.08 NA NA NA
#> 2 age, Cure model 0.0189 NA NA NA
#> 3 grade_ii, Cure model 0.197 NA NA NA
#> 4 grade_iii, Cure model 1.22 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0116 NA NA NA
#> 2 grade_ii, Survival model 0.294 NA NA NA
#> 3 grade_iii, Survival model 0.304 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.07574 0.01891 0.19651 1.22092
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 246.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.07573894 0.01890611 0.19651332 1.22092007
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01164842 0.29377687 0.30421117
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0282636089 0.0153217667 0.4653326244 0.1111200413 0.4225571138
#> [6] 0.6702262114 0.6118242665 0.0752400286 0.0042249355 0.1720428139
#> [11] 0.1111200413 0.3201435228 0.1976833707 0.2521473471 0.3912302792
#> [16] 0.3808502555 0.4979866354 0.5200387834 0.5424924310 0.5885147927
#> [21] 0.2240174130 0.0962365800 0.9865980980 0.0443712231 0.1720428139
#> [26] 0.3003302301 0.4653326244 0.4979866354 0.6118242665 0.7796428152
#> [31] 0.7302588775 0.2333106161 0.0557017008 0.1976833707 0.1889307128
#> [36] 0.2717687775 0.7548237861 0.6702262114 0.0752400286 0.8428146547
#> [41] 0.0042249355 0.4225571138 0.6582415440 0.6942033661 0.0685632323
#> [46] 0.2333106161 0.8048656533 0.1036133260 0.0153217667 0.9206990137
#> [51] 0.7425476981 0.0008906467 0.9206990137 0.8048656533 0.0106209456
#> [56] 0.5652763528 0.8048656533 0.3507519714 0.9471127356 0.2717687775
#> [61] 0.0153217667 0.5424924310 0.2619289861 0.6118242665 0.5652763528
#> [66] 0.4016893547 0.4016893547 0.9075507705 0.1111200413 0.3003302301
#> [71] 0.1111200413 0.2717687775 0.5200387834 0.1637112756 0.4869553172
#> [76] 0.1976833707 0.7796428152 0.0282636089 0.0443712231 0.3302855451
#> [81] 0.4544536773 0.8428146547 0.6118242665 0.0889324487 0.5885147927
#> [86] 0.8815886506 0.3507519714 0.1394986474 0.1554548305 0.8815886506
#> [91] 0.9471127356 0.3404774041 0.9471127356 0.1473842396 0.7548237861
#> [96] 0.6942033661 0.0620009395 0.3507519714 0.4436689957 0.0385056443
#> [101] 0.6942033661 0.0008906467 0.8685679008 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 92 129 39 190 26 155 57 197 168 55 190.1 106 97
#> 22.92 23.41 15.59 20.81 15.77 13.08 14.46 21.60 23.72 19.34 20.81 16.67 19.14
#> 51 79 5 18 157 180 96 179 99 91 194 55.1 184
#> 18.23 16.23 16.43 15.21 15.10 14.82 14.54 18.63 21.19 5.33 22.40 19.34 17.77
#> 39.1 18.1 57.1 56 140 88 66 97.1 76 40 177 155.1 197.1
#> 15.59 15.21 14.46 12.21 12.68 18.37 22.13 19.14 19.22 18.00 12.53 13.08 21.60
#> 43 168.1 26.1 13 14 136 88.1 49 90 129.1 16 154 24
#> 12.10 23.72 15.77 14.34 12.89 21.83 18.37 12.19 20.94 23.41 8.71 12.63 23.89
#> 16.1 49.1 164 133 49.2 192 149 40.1 129.2 180.1 41 57.2 133.1
#> 8.71 12.19 23.60 14.65 12.19 16.44 8.37 18.00 23.41 14.82 18.02 14.46 14.65
#> 188 188.1 183 190.2 184.1 190.3 40.2 157.1 170 29 97.2 56.1 92.1
#> 16.16 16.16 9.24 20.81 17.77 20.81 18.00 15.10 19.54 15.45 19.14 12.21 22.92
#> 194.1 171 6 43.1 57.3 153 96.1 187 192.1 68 158 187.1 149.1
#> 22.40 16.57 15.64 12.10 14.46 21.33 14.54 9.92 16.44 20.62 20.14 9.92 8.37
#> 130 149.2 150 177.1 14.1 175 192.2 125 169 14.2 24.1 159 34
#> 16.47 8.37 20.33 12.53 12.89 21.91 16.44 15.65 22.41 12.89 23.89 10.55 24.00
#> 156 35 109 38 80 185 28 178 142 34.1 109.1 163 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 144 71 1 53 142.1 116 98 156.1 67 103 172 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 75 21 83 156.2 87 71.1 178.1 87.1 109.2 126 17 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 174 7 54 186 146 137 20 7.1 102 64 174.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 21.1 95 118 147 172.1 83.1 141 138 162 118.1 143 109.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 64.1 74 19 172.2 193 74.1 47 9 182 196 87.2 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 132.1 83.2 156.3 141.1 178.2 122 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[21]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004161586 0.810497719 0.655422691
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.226590269 0.002680734 -0.143991208
#> grade_iii, Cure model
#> 1.119902059
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 187 9.92 1 39 1 0
#> 164 23.60 1 76 0 1
#> 175 21.91 1 43 0 0
#> 56 12.21 1 60 0 0
#> 52 10.42 1 52 0 1
#> 41 18.02 1 40 1 0
#> 24 23.89 1 38 0 0
#> 10 10.53 1 34 0 0
#> 188 16.16 1 46 0 1
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 113 22.86 1 34 0 0
#> 36 21.19 1 48 0 1
#> 192 16.44 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 192.1 16.44 1 31 1 0
#> 139 21.49 1 63 1 0
#> 15 22.68 1 48 0 0
#> 96 14.54 1 33 0 1
#> 56.1 12.21 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 14 12.89 1 21 0 0
#> 36.2 21.19 1 48 0 1
#> 78 23.88 1 43 0 0
#> 93 10.33 1 52 0 1
#> 68.1 20.62 1 44 0 0
#> 93.1 10.33 1 52 0 1
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 183 9.24 1 67 1 0
#> 25 6.32 1 34 1 0
#> 189 10.51 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 97.1 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 88 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 199 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 16.1 8.71 1 71 0 1
#> 180 14.82 1 37 0 0
#> 179 18.63 1 42 0 0
#> 168 23.72 1 70 0 0
#> 167 15.55 1 56 1 0
#> 106 16.67 1 49 1 0
#> 6 15.64 1 39 0 0
#> 25.1 6.32 1 34 1 0
#> 58 19.34 1 39 0 0
#> 68.2 20.62 1 44 0 0
#> 86 23.81 1 58 0 1
#> 91.1 5.33 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 192.2 16.44 1 31 1 0
#> 192.3 16.44 1 31 1 0
#> 45 17.42 1 54 0 1
#> 190 20.81 1 42 1 0
#> 57 14.46 1 45 0 1
#> 175.1 21.91 1 43 0 0
#> 55 19.34 1 69 0 1
#> 150 20.33 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 8 18.43 1 32 0 0
#> 181 16.46 1 45 0 1
#> 93.2 10.33 1 52 0 1
#> 124.1 9.73 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 63 22.77 1 31 1 0
#> 99 21.19 1 38 0 1
#> 175.2 21.91 1 43 0 0
#> 39.1 15.59 1 37 0 1
#> 167.1 15.55 1 56 1 0
#> 180.1 14.82 1 37 0 0
#> 16.2 8.71 1 71 0 1
#> 43.1 12.10 1 61 0 1
#> 40 18.00 1 28 1 0
#> 134 17.81 1 47 1 0
#> 86.1 23.81 1 58 0 1
#> 134.1 17.81 1 47 1 0
#> 195 11.76 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 190.1 20.81 1 42 1 0
#> 79 16.23 1 54 1 0
#> 81 14.06 1 34 0 0
#> 179.2 18.63 1 42 0 0
#> 158 20.14 1 74 1 0
#> 107 11.18 1 54 1 0
#> 125 15.65 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 76.2 19.22 1 54 0 1
#> 5 16.43 1 51 0 1
#> 105 19.75 1 60 0 0
#> 189.1 10.51 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 130.1 16.47 1 53 0 1
#> 149 8.37 1 33 1 0
#> 57.1 14.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 15.1 22.68 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 77 7.27 1 67 0 1
#> 105.1 19.75 1 60 0 0
#> 8.1 18.43 1 32 0 0
#> 81.1 14.06 1 34 0 0
#> 78.1 23.88 1 43 0 0
#> 155 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 15.2 22.68 1 48 0 0
#> 195.1 11.76 1 NA 1 0
#> 20 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 103 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 33 24.00 0 53 0 0
#> 82.1 24.00 0 34 0 0
#> 38 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 109 24.00 0 48 0 0
#> 33.1 24.00 0 53 0 0
#> 20.1 24.00 0 46 1 0
#> 122 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 53 24.00 0 32 0 1
#> 33.2 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 20.2 24.00 0 46 1 0
#> 119 24.00 0 17 0 0
#> 71 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 34.1 24.00 0 36 0 0
#> 20.3 24.00 0 46 1 0
#> 21 24.00 0 47 0 0
#> 200.1 24.00 0 64 0 0
#> 121 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 33.3 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 131 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 109.1 24.00 0 48 0 0
#> 151 24.00 0 42 0 0
#> 193.1 24.00 0 45 0 1
#> 19 24.00 0 57 0 1
#> 87 24.00 0 27 0 0
#> 137 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 87.1 24.00 0 27 0 0
#> 148.1 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 38.1 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 103.1 24.00 0 56 1 0
#> 163 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 122.1 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 186 24.00 0 45 1 0
#> 138.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 54 24.00 0 53 1 0
#> 146.1 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 75 24.00 0 21 1 0
#> 121.1 24.00 0 57 1 0
#> 19.1 24.00 0 57 0 1
#> 142.1 24.00 0 53 0 0
#> 196 24.00 0 19 0 0
#> 71.1 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 33.4 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 31 24.00 0 36 0 1
#> 119.1 24.00 0 17 0 0
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 46 24.00 0 71 0 0
#> 84.2 24.00 0 39 0 1
#> 141.1 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 152.1 24.00 0 36 0 1
#> 116 24.00 0 58 0 1
#> 75.1 24.00 0 21 1 0
#> 75.2 24.00 0 21 1 0
#> 67.1 24.00 0 25 0 0
#> 54.1 24.00 0 53 1 0
#> 95 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 137.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.227 NA NA NA
#> 2 age, Cure model 0.00268 NA NA NA
#> 3 grade_ii, Cure model -0.144 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00416 NA NA NA
#> 2 grade_ii, Survival model 0.810 NA NA NA
#> 3 grade_iii, Survival model 0.655 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.226590 0.002681 -0.143991 1.119902
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 249 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.226590269 0.002680734 -0.143991208 1.119902059
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004161586 0.810497719 0.655422691
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.783893697 0.921074370 0.116463569 0.207473938 0.837903751 0.883800344
#> [7] 0.535801740 0.008588496 0.876179434 0.679793571 0.321366975 0.913636342
#> [13] 0.426172740 0.144617766 0.257856540 0.629556345 0.456125499 0.629556345
#> [19] 0.245110634 0.170938094 0.760445510 0.837903751 0.257856540 0.822440718
#> [25] 0.257856540 0.027708913 0.891385206 0.321366975 0.891385206 0.574508370
#> [31] 0.985970731 0.928458015 0.971842124 0.712743298 0.456125499 0.853303563
#> [37] 0.525634721 0.935800682 0.688104141 0.935800682 0.744603484 0.475908197
#> [43] 0.087684763 0.728809424 0.593297904 0.704543424 0.971842124 0.395043641
#> [49] 0.321366975 0.061161069 0.985970731 0.629556345 0.629556345 0.583943818
#> [55] 0.300559870 0.768352014 0.207473938 0.395043641 0.352567496 0.475908197
#> [61] 0.505565636 0.620555888 0.891385206 0.783893697 0.158310743 0.257856540
#> [67] 0.207473938 0.712743298 0.728809424 0.744603484 0.935800682 0.853303563
#> [73] 0.545797281 0.555612777 0.061161069 0.555612777 0.602530574 0.300559870
#> [79] 0.671422583 0.799271270 0.475908197 0.363349893 0.868567260 0.696357825
#> [85] 0.426172740 0.426172740 0.662967650 0.373927386 0.395043641 0.602530574
#> [91] 0.957437390 0.768352014 0.087684763 0.170938094 0.830199572 0.964652053
#> [97] 0.373927386 0.505565636 0.799271270 0.027708913 0.814687985 0.131094551
#> [103] 0.170938094 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 13 187 164 175 56 52 41 24 10 188 68 61 76
#> 14.34 9.92 23.60 21.91 12.21 10.42 18.02 23.89 10.53 16.16 20.62 10.12 19.22
#> 113 36 192 97 192.1 139 15 96 56.1 36.1 14 36.2 78
#> 22.86 21.19 16.44 19.14 16.44 21.49 22.68 14.54 12.21 21.19 12.89 21.19 23.88
#> 93 68.1 93.1 111 91 183 25 39 97.1 43 88 16 26
#> 10.33 20.62 10.33 17.45 5.33 9.24 6.32 15.59 19.14 12.10 18.37 8.71 15.77
#> 16.1 180 179 168 167 106 6 25.1 58 68.2 86 91.1 192.2
#> 8.71 14.82 18.63 23.72 15.55 16.67 15.64 6.32 19.34 20.62 23.81 5.33 16.44
#> 192.3 45 190 57 175.1 55 150 179.1 8 181 93.2 13.1 63
#> 16.44 17.42 20.81 14.46 21.91 19.34 20.33 18.63 18.43 16.46 10.33 14.34 22.77
#> 99 175.2 39.1 167.1 180.1 16.2 43.1 40 134 86.1 134.1 130 190.1
#> 21.19 21.91 15.59 15.55 14.82 8.71 12.10 18.00 17.81 23.81 17.81 16.47 20.81
#> 79 81 179.2 158 107 125 76.1 76.2 5 105 58.1 130.1 149
#> 16.23 14.06 18.63 20.14 11.18 15.65 19.22 19.22 16.43 19.75 19.34 16.47 8.37
#> 57.1 168.1 15.1 140 77 105.1 8.1 81.1 78.1 155 69 15.2 20
#> 14.46 23.72 22.68 12.68 7.27 19.75 18.43 14.06 23.88 13.08 23.23 22.68 24.00
#> 200 103 82 33 82.1 38 7 109 33.1 20.1 122 193 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.2 62 20.2 119 71 34 11 146 34.1 20.3 21 200.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 33.3 152 148 131 67 109.1 151 193.1 19 87 137 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 148.1 141 38.1 44 103.1 163 165 126 142 122.1 161 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 74 64 54 146.1 98 75 121.1 19.1 142.1 196 71.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.4 31 119.1 84 84.1 46 84.2 141.1 44.1 152.1 116 75.1 75.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 54.1 95 28 137.1 48 185 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[22]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02010454 0.43990041 0.02590773
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.479719401 -0.007635197 -0.547189945
#> grade_iii, Cure model
#> 0.667037406
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 149 8.37 1 33 1 0
#> 105 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 168 23.72 1 70 0 0
#> 39 15.59 1 37 0 1
#> 117 17.46 1 26 0 1
#> 164 23.60 1 76 0 1
#> 81 14.06 1 34 0 0
#> 117.1 17.46 1 26 0 1
#> 26 15.77 1 49 0 1
#> 39.1 15.59 1 37 0 1
#> 89 11.44 1 NA 0 0
#> 13 14.34 1 54 0 1
#> 99 21.19 1 38 0 1
#> 114 13.68 1 NA 0 0
#> 93 10.33 1 52 0 1
#> 70 7.38 1 30 1 0
#> 70.1 7.38 1 30 1 0
#> 149.1 8.37 1 33 1 0
#> 61 10.12 1 36 0 1
#> 189 10.51 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 181 16.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 68 20.62 1 44 0 0
#> 139 21.49 1 63 1 0
#> 89.1 11.44 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 61.1 10.12 1 36 0 1
#> 136 21.83 1 43 0 1
#> 39.2 15.59 1 37 0 1
#> 181.1 16.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 32 20.90 1 37 1 0
#> 197 21.60 1 69 1 0
#> 8 18.43 1 32 0 0
#> 92 22.92 1 47 0 1
#> 10 10.53 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 127 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 197.1 21.60 1 69 1 0
#> 101 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 86 23.81 1 58 0 1
#> 180 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 93.1 10.33 1 52 0 1
#> 13.1 14.34 1 54 0 1
#> 6.1 15.64 1 39 0 0
#> 88 18.37 1 47 0 0
#> 189.1 10.51 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 8.1 18.43 1 32 0 0
#> 57.1 14.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 164.1 23.60 1 76 0 1
#> 88.1 18.37 1 47 0 0
#> 180.1 14.82 1 37 0 0
#> 61.2 10.12 1 36 0 1
#> 177 12.53 1 75 0 0
#> 155 13.08 1 26 0 0
#> 140 12.68 1 59 1 0
#> 183 9.24 1 67 1 0
#> 70.2 7.38 1 30 1 0
#> 170 19.54 1 43 0 1
#> 180.2 14.82 1 37 0 0
#> 6.2 15.64 1 39 0 0
#> 189.2 10.51 1 NA 1 0
#> 93.2 10.33 1 52 0 1
#> 57.2 14.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 57.3 14.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 139.1 21.49 1 63 1 0
#> 13.2 14.34 1 54 0 1
#> 63 22.77 1 31 1 0
#> 150 20.33 1 48 0 0
#> 166 19.98 1 48 0 0
#> 155.1 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 29 15.45 1 68 1 0
#> 175 21.91 1 43 0 0
#> 5 16.43 1 51 0 1
#> 32.1 20.90 1 37 1 0
#> 92.1 22.92 1 47 0 1
#> 127.1 3.53 1 62 0 1
#> 158 20.14 1 74 1 0
#> 92.2 22.92 1 47 0 1
#> 110 17.56 1 65 0 1
#> 4.1 17.64 1 NA 0 1
#> 92.3 22.92 1 47 0 1
#> 50.1 10.02 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 125.1 15.65 1 67 1 0
#> 157 15.10 1 47 0 0
#> 81.1 14.06 1 34 0 0
#> 105.1 19.75 1 60 0 0
#> 23 16.92 1 61 0 0
#> 15 22.68 1 48 0 0
#> 100 16.07 1 60 0 0
#> 184.1 17.77 1 38 0 0
#> 180.3 14.82 1 37 0 0
#> 136.1 21.83 1 43 0 1
#> 92.4 22.92 1 47 0 1
#> 26.1 15.77 1 49 0 1
#> 6.3 15.64 1 39 0 0
#> 140.1 12.68 1 59 1 0
#> 192 16.44 1 31 1 0
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 161 24.00 0 45 0 0
#> 74 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 98 24.00 0 34 1 0
#> 132 24.00 0 55 0 0
#> 53 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 186 24.00 0 45 1 0
#> 38 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 131 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 174.1 24.00 0 49 1 0
#> 174.2 24.00 0 49 1 0
#> 11 24.00 0 42 0 1
#> 3 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 22 24.00 0 52 1 0
#> 19.1 24.00 0 57 0 1
#> 95 24.00 0 68 0 1
#> 65.1 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 143 24.00 0 51 0 0
#> 12.1 24.00 0 63 0 0
#> 98.1 24.00 0 34 1 0
#> 46 24.00 0 71 0 0
#> 46.1 24.00 0 71 0 0
#> 174.3 24.00 0 49 1 0
#> 94.1 24.00 0 51 0 1
#> 38.1 24.00 0 31 1 0
#> 65.2 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 104 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#> 94.2 24.00 0 51 0 1
#> 84 24.00 0 39 0 1
#> 135.1 24.00 0 58 1 0
#> 160 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 163 24.00 0 66 0 0
#> 33.1 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 11.1 24.00 0 42 0 1
#> 74.1 24.00 0 43 0 1
#> 65.3 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 152 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 12.2 24.00 0 63 0 0
#> 135.2 24.00 0 58 1 0
#> 3.1 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 44.1 24.00 0 56 0 0
#> 132.1 24.00 0 55 0 0
#> 174.4 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 11.2 24.00 0 42 0 1
#> 64 24.00 0 43 0 0
#> 2 24.00 0 9 0 0
#> 62 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#> 21 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 17.1 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 46.2 24.00 0 71 0 0
#> 162.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 137.1 24.00 0 45 1 0
#> 135.3 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.480 NA NA NA
#> 2 age, Cure model -0.00764 NA NA NA
#> 3 grade_ii, Cure model -0.547 NA NA NA
#> 4 grade_iii, Cure model 0.667 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0201 NA NA NA
#> 2 grade_ii, Survival model 0.440 NA NA NA
#> 3 grade_iii, Survival model 0.0259 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.479719 -0.007635 -0.547190 0.667037
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 248.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.479719401 -0.007635197 -0.547189945 0.667037406
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02010454 0.43990041 0.02590773
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 8.578022e-01 6.613026e-02 1.072374e-01 1.145374e-04 3.043026e-01
#> [6] 1.351199e-01 3.022991e-04 5.334599e-01 1.351199e-01 2.200284e-01
#> [11] 3.043026e-01 4.874612e-01 2.625599e-02 6.673210e-01 8.979865e-01
#> [16] 8.979865e-01 8.578022e-01 7.218094e-01 3.521306e-01 2.625599e-02
#> [21] 7.733991e-03 1.664002e-01 7.784466e-01 3.988464e-02 2.045893e-02
#> [26] 2.398321e-01 7.218094e-01 1.129347e-02 3.043026e-01 1.664002e-01
#> [31] 4.769202e-02 3.288351e-02 1.546191e-02 8.252240e-02 1.172245e-03
#> [36] 6.495926e-01 3.988464e-02 9.581863e-01 2.606619e-01 1.546191e-02
#> [41] 7.980862e-01 1.581335e-01 3.207122e-05 3.777555e-01 4.305662e-01
#> [46] 6.673210e-01 4.874612e-01 2.606619e-01 9.438574e-02 1.834918e-01
#> [51] 8.252240e-02 4.305662e-01 3.022991e-04 9.438574e-02 3.777555e-01
#> [56] 7.218094e-01 6.321006e-01 5.655106e-01 5.983184e-01 8.376606e-01
#> [61] 8.979865e-01 7.676960e-02 3.777555e-01 2.606619e-01 6.673210e-01
#> [66] 4.305662e-01 8.178037e-01 4.305662e-01 2.045893e-02 4.874612e-01
#> [71] 4.951620e-03 5.194937e-02 6.116340e-02 5.655106e-01 3.747808e-06
#> [76] 3.396445e-01 9.416475e-03 2.011454e-01 3.288351e-02 1.172245e-03
#> [81] 9.581863e-01 5.643433e-02 1.172245e-03 1.277224e-01 1.172245e-03
#> [86] 1.139162e-01 2.398321e-01 3.648055e-01 5.334599e-01 6.613026e-02
#> [91] 1.501371e-01 6.247128e-03 2.104385e-01 1.139162e-01 3.777555e-01
#> [96] 1.129347e-02 1.172245e-03 2.200284e-01 2.606619e-01 5.983184e-01
#> [101] 1.834918e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 149 105 40 168 39 117 164 81 117.1 26 39.1 13 99
#> 8.37 19.75 18.00 23.72 15.59 17.46 23.60 14.06 17.46 15.77 15.59 14.34 21.19
#> 93 70 70.1 149.1 61 18 36 169 181 145 68 139 125
#> 10.33 7.38 7.38 8.37 10.12 15.21 21.19 22.41 16.46 10.07 20.62 21.49 15.65
#> 61.1 136 39.2 181.1 128 32 197 8 92 10 68.1 127 6
#> 10.12 21.83 15.59 16.46 20.35 20.90 21.60 18.43 22.92 10.53 20.62 3.53 15.64
#> 197.1 101 130 86 180 57 93.1 13.1 6.1 88 85 8.1 57.1
#> 21.60 9.97 16.47 23.81 14.82 14.46 10.33 14.34 15.64 18.37 16.44 18.43 14.46
#> 164.1 88.1 180.1 61.2 177 155 140 183 70.2 170 180.2 6.2 93.2
#> 23.60 18.37 14.82 10.12 12.53 13.08 12.68 9.24 7.38 19.54 14.82 15.64 10.33
#> 57.2 187 57.3 139.1 13.2 63 150 166 155.1 24 29 175 5
#> 14.46 9.92 14.46 21.49 14.34 22.77 20.33 19.98 13.08 23.89 15.45 21.91 16.43
#> 32.1 92.1 127.1 158 92.2 110 92.3 184 125.1 157 81.1 105.1 23
#> 20.90 22.92 3.53 20.14 22.92 17.56 22.92 17.77 15.65 15.10 14.06 19.75 16.92
#> 15 100 184.1 180.3 136.1 92.4 26.1 6.3 140.1 192 65 121 12
#> 22.68 16.07 17.77 14.82 21.83 22.92 15.77 15.64 12.68 16.44 24.00 24.00 24.00
#> 174 161 74 120 80 148 98 132 53 17 94 186 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 131 19 72 174.1 174.2 11 3 148.1 22 19.1 95 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 143 12.1 98.1 46 46.1 174.3 94.1 38.1 65.2 33 178 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.1 94.2 84 135.1 160 82 163 33.1 137 162 141 80.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 65.3 118 48 152 138 165 12.2 135.2 3.1 54 44.1 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.4 173 11.2 64 2 62 196 21 172 1 17.1 186.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.2 162.1 182 137.1 135.3 156
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[23]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002076225 0.907714763 0.600265363
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.197255837 -0.005742178 -0.126001433
#> grade_iii, Cure model
#> 0.810620876
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 197 21.60 1 69 1 0
#> 60 13.15 1 38 1 0
#> 113 22.86 1 34 0 0
#> 145 10.07 1 65 1 0
#> 130 16.47 1 53 0 1
#> 60.1 13.15 1 38 1 0
#> 6 15.64 1 39 0 0
#> 40 18.00 1 28 1 0
#> 25 6.32 1 34 1 0
#> 139 21.49 1 63 1 0
#> 199 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 199.1 19.81 1 NA 0 1
#> 66 22.13 1 53 0 0
#> 24 23.89 1 38 0 0
#> 13 14.34 1 54 0 1
#> 42 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 166 19.98 1 48 0 0
#> 90 20.94 1 50 0 1
#> 140 12.68 1 59 1 0
#> 91 5.33 1 61 0 1
#> 69 23.23 1 25 0 1
#> 70 7.38 1 30 1 0
#> 187 9.92 1 39 1 0
#> 154 12.63 1 20 1 0
#> 70.1 7.38 1 30 1 0
#> 89 11.44 1 NA 0 0
#> 25.1 6.32 1 34 1 0
#> 190 20.81 1 42 1 0
#> 63 22.77 1 31 1 0
#> 76 19.22 1 54 0 1
#> 69.1 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 6.1 15.64 1 39 0 0
#> 45 17.42 1 54 0 1
#> 42.1 12.43 1 49 0 1
#> 149 8.37 1 33 1 0
#> 15 22.68 1 48 0 0
#> 184 17.77 1 38 0 0
#> 105 19.75 1 60 0 0
#> 164 23.60 1 76 0 1
#> 16 8.71 1 71 0 1
#> 76.1 19.22 1 54 0 1
#> 168 23.72 1 70 0 0
#> 199.2 19.81 1 NA 0 1
#> 188 16.16 1 46 0 1
#> 26 15.77 1 49 0 1
#> 166.1 19.98 1 48 0 0
#> 107 11.18 1 54 1 0
#> 5 16.43 1 51 0 1
#> 150 20.33 1 48 0 0
#> 133 14.65 1 57 0 0
#> 188.1 16.16 1 46 0 1
#> 133.1 14.65 1 57 0 0
#> 184.1 17.77 1 38 0 0
#> 179.1 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 59.1 10.16 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 70.2 7.38 1 30 1 0
#> 79 16.23 1 54 1 0
#> 13.1 14.34 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 179.2 18.63 1 42 0 0
#> 130.1 16.47 1 53 0 1
#> 77 7.27 1 67 0 1
#> 24.1 23.89 1 38 0 0
#> 167 15.55 1 56 1 0
#> 29 15.45 1 68 1 0
#> 70.3 7.38 1 30 1 0
#> 51 18.23 1 83 0 1
#> 55 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 133.2 14.65 1 57 0 0
#> 40.1 18.00 1 28 1 0
#> 183 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 133.3 14.65 1 57 0 0
#> 26.1 15.77 1 49 0 1
#> 124.1 9.73 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 190.1 20.81 1 42 1 0
#> 127 3.53 1 62 0 1
#> 177 12.53 1 75 0 0
#> 42.2 12.43 1 49 0 1
#> 59.2 10.16 1 NA 1 0
#> 24.2 23.89 1 38 0 0
#> 96.1 14.54 1 33 0 1
#> 195.1 11.76 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 36 21.19 1 48 0 1
#> 117 17.46 1 26 0 1
#> 114 13.68 1 NA 0 0
#> 150.1 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 13.2 14.34 1 54 0 1
#> 13.3 14.34 1 54 0 1
#> 37 12.52 1 57 1 0
#> 13.4 14.34 1 54 0 1
#> 96.2 14.54 1 33 0 1
#> 55.1 19.34 1 69 0 1
#> 158 20.14 1 74 1 0
#> 77.1 7.27 1 67 0 1
#> 155 13.08 1 26 0 0
#> 29.1 15.45 1 68 1 0
#> 1 24.00 0 23 1 0
#> 156 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 38 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 137 24.00 0 45 1 0
#> 186 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 82 24.00 0 34 0 0
#> 104 24.00 0 50 1 0
#> 38.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 95 24.00 0 68 0 1
#> 48 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 54 24.00 0 53 1 0
#> 27.1 24.00 0 63 1 0
#> 103 24.00 0 56 1 0
#> 22.1 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 22.2 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 21 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 21.1 24.00 0 47 0 0
#> 186.1 24.00 0 45 1 0
#> 17 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 121 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 172 24.00 0 41 0 0
#> 182.1 24.00 0 35 0 0
#> 34 24.00 0 36 0 0
#> 2 24.00 0 9 0 0
#> 163.1 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 173 24.00 0 19 0 1
#> 98 24.00 0 34 1 0
#> 186.2 24.00 0 45 1 0
#> 112.1 24.00 0 61 0 0
#> 135.2 24.00 0 58 1 0
#> 71.2 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 27.2 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 19 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 72 24.00 0 40 0 1
#> 28 24.00 0 67 1 0
#> 64 24.00 0 43 0 0
#> 121.1 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#> 173.1 24.00 0 19 0 1
#> 74.1 24.00 0 43 0 1
#> 38.2 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 161 24.00 0 45 0 0
#> 119 24.00 0 17 0 0
#> 151 24.00 0 42 0 0
#> 120.1 24.00 0 68 0 1
#> 112.2 24.00 0 61 0 0
#> 33 24.00 0 53 0 0
#> 1.1 24.00 0 23 1 0
#> 186.3 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.197 NA NA NA
#> 2 age, Cure model -0.00574 NA NA NA
#> 3 grade_ii, Cure model -0.126 NA NA NA
#> 4 grade_iii, Cure model 0.811 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00208 NA NA NA
#> 2 grade_ii, Survival model 0.908 NA NA NA
#> 3 grade_iii, Survival model 0.600 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.197256 -0.005742 -0.126001 0.810621
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.6
#> Residual Deviance: 251.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.197255837 -0.005742178 -0.126001433 0.810620876
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002076225 0.907714763 0.600265363
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.31638806 0.83464634 0.22415689 0.91980318 0.62586343 0.83464634
#> [7] 0.71216792 0.57368027 0.97947263 0.33240639 0.52613366 0.64238524
#> [13] 0.40993171 0.29870471 0.05016664 0.79604714 0.89053764 0.56439880
#> [19] 0.45451383 0.37376010 0.85998285 0.98976557 0.18485989 0.94791068
#> [25] 0.92553567 0.87229626 0.94791068 0.97947263 0.38683632 0.26297485
#> [31] 0.50671271 0.18485989 0.65059359 0.71216792 0.61731218 0.89053764
#> [37] 0.94239178 0.28089910 0.59117937 0.47576949 0.15863706 0.93681888
#> [43] 0.50671271 0.12640434 0.68226932 0.69738167 0.45451383 0.91400431
#> [49] 0.66656222 0.42133404 0.74820009 0.68226932 0.74820009 0.59117937
#> [55] 0.52613366 0.77578313 0.85363973 0.94791068 0.67449681 0.79604714
#> [61] 0.52613366 0.62586343 0.96899695 0.05016664 0.72692833 0.73421374
#> [67] 0.94791068 0.55485148 0.48648663 0.34713017 0.74820009 0.57368027
#> [73] 0.93120887 0.65059359 0.74820009 0.69738167 0.22415689 0.38683632
#> [79] 0.99489691 0.87840631 0.89053764 0.05016664 0.77578313 0.85998285
#> [85] 0.82813142 0.34713017 0.60863609 0.42133404 0.90813947 0.79604714
#> [91] 0.79604714 0.88450921 0.79604714 0.77578313 0.48648663 0.44370525
#> [97] 0.96899695 0.84729451 0.73421374 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 197 60 113 145 130 60.1 6 40 25 139 179 181 128
#> 21.60 13.15 22.86 10.07 16.47 13.15 15.64 18.00 6.32 21.49 18.63 16.46 20.35
#> 66 24 13 42 41 166 90 140 91 69 70 187 154
#> 22.13 23.89 14.34 12.43 18.02 19.98 20.94 12.68 5.33 23.23 7.38 9.92 12.63
#> 70.1 25.1 190 63 76 69.1 85 6.1 45 42.1 149 15 184
#> 7.38 6.32 20.81 22.77 19.22 23.23 16.44 15.64 17.42 12.43 8.37 22.68 17.77
#> 105 164 16 76.1 168 188 26 166.1 107 5 150 133 188.1
#> 19.75 23.60 8.71 19.22 23.72 16.16 15.77 19.98 11.18 16.43 20.33 14.65 16.16
#> 133.1 184.1 179.1 96 14 70.2 79 13.1 179.2 130.1 77 24.1 167
#> 14.65 17.77 18.63 14.54 12.89 7.38 16.23 14.34 18.63 16.47 7.27 23.89 15.55
#> 29 70.3 51 55 99 133.2 40.1 183 192 133.3 26.1 113.1 190.1
#> 15.45 7.38 18.23 19.34 21.19 14.65 18.00 9.24 16.44 14.65 15.77 22.86 20.81
#> 127 177 42.2 24.2 96.1 140.1 81 36 117 150.1 43 13.2 13.3
#> 3.53 12.53 12.43 23.89 14.54 12.68 14.06 21.19 17.46 20.33 12.10 14.34 14.34
#> 37 13.4 96.2 55.1 158 77.1 155 29.1 1 156 135 46 147
#> 12.52 14.34 14.54 19.34 20.14 7.27 13.08 15.45 24.00 24.00 24.00 24.00 24.00
#> 147.1 38 146 182 137 186 163 47 35 71 122 71.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 82 104 38.1 65 27 112 95 48 67 162 22 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 27.1 103 22.1 95.1 22.2 193 21 3 135.1 21.1 186.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 121 148 172 182.1 34 2 163.1 120 7 83 11 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 186.2 112.1 135.2 71.2 162.1 178 165 27.2 47.1 138 116.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 72 28 64 121.1 46.1 173.1 74.1 38.2 148.1 161 119 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 112.2 33 1.1 186.3
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[24]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0005747655 0.7754530877 0.5288412721
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.79701491 0.02847571 0.73676004
#> grade_iii, Cure model
#> 1.18809428
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 150 20.33 1 48 0 0
#> 18 15.21 1 49 1 0
#> 188 16.16 1 46 0 1
#> 192 16.44 1 31 1 0
#> 43 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 190 20.81 1 42 1 0
#> 43.1 12.10 1 61 0 1
#> 60 13.15 1 38 1 0
#> 8 18.43 1 32 0 0
#> 125 15.65 1 67 1 0
#> 55 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 164 23.60 1 76 0 1
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 24.2 23.89 1 38 0 0
#> 155 13.08 1 26 0 0
#> 199 19.81 1 NA 0 1
#> 60.1 13.15 1 38 1 0
#> 153 21.33 1 55 1 0
#> 194 22.40 1 38 0 1
#> 18.1 15.21 1 49 1 0
#> 100 16.07 1 60 0 0
#> 60.2 13.15 1 38 1 0
#> 51 18.23 1 83 0 1
#> 52 10.42 1 52 0 1
#> 26 15.77 1 49 0 1
#> 170 19.54 1 43 0 1
#> 111 17.45 1 47 0 1
#> 168 23.72 1 70 0 0
#> 52.1 10.42 1 52 0 1
#> 199.1 19.81 1 NA 0 1
#> 158 20.14 1 74 1 0
#> 105.1 19.75 1 60 0 0
#> 51.1 18.23 1 83 0 1
#> 5 16.43 1 51 0 1
#> 158.1 20.14 1 74 1 0
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 79 16.23 1 54 1 0
#> 69 23.23 1 25 0 1
#> 139.1 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 192.1 16.44 1 31 1 0
#> 49 12.19 1 48 1 0
#> 89 11.44 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 105.2 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 30 17.43 1 78 0 0
#> 97 19.14 1 65 0 1
#> 183 9.24 1 67 1 0
#> 105.3 19.75 1 60 0 0
#> 99 21.19 1 38 0 1
#> 199.2 19.81 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 134 17.81 1 47 1 0
#> 106 16.67 1 49 1 0
#> 43.2 12.10 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 159.1 10.55 1 50 0 1
#> 29 15.45 1 68 1 0
#> 77 7.27 1 67 0 1
#> 180 14.82 1 37 0 0
#> 177 12.53 1 75 0 0
#> 69.1 23.23 1 25 0 1
#> 49.1 12.19 1 48 1 0
#> 4 17.64 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 107 11.18 1 54 1 0
#> 92 22.92 1 47 0 1
#> 51.2 18.23 1 83 0 1
#> 167 15.55 1 56 1 0
#> 154 12.63 1 20 1 0
#> 139.2 21.49 1 63 1 0
#> 25 6.32 1 34 1 0
#> 77.1 7.27 1 67 0 1
#> 108 18.29 1 39 0 1
#> 154.1 12.63 1 20 1 0
#> 59.1 10.16 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 59.2 10.16 1 NA 1 0
#> 51.3 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 183.1 9.24 1 67 1 0
#> 25.1 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 39 15.59 1 37 0 1
#> 99.1 21.19 1 38 0 1
#> 177.1 12.53 1 75 0 0
#> 79.1 16.23 1 54 1 0
#> 170.1 19.54 1 43 0 1
#> 57 14.46 1 45 0 1
#> 43.3 12.10 1 61 0 1
#> 13 14.34 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 123 13.00 1 44 1 0
#> 100.2 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 140 12.68 1 59 1 0
#> 60.3 13.15 1 38 1 0
#> 45 17.42 1 54 0 1
#> 85 16.44 1 36 0 0
#> 169 22.41 1 46 0 0
#> 70 7.38 1 30 1 0
#> 149 8.37 1 33 1 0
#> 117 17.46 1 26 0 1
#> 129 23.41 1 53 1 0
#> 178 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 27 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 162 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 98 24.00 0 34 1 0
#> 53 24.00 0 32 0 1
#> 112 24.00 0 61 0 0
#> 142.1 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 121.1 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 172 24.00 0 41 0 0
#> 200 24.00 0 64 0 0
#> 102 24.00 0 49 0 0
#> 119 24.00 0 17 0 0
#> 53.1 24.00 0 32 0 1
#> 104 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 112.1 24.00 0 61 0 0
#> 142.2 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 87 24.00 0 27 0 0
#> 185 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 173 24.00 0 19 0 1
#> 182.1 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 104.1 24.00 0 50 1 0
#> 46.1 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 33 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 35.1 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 7 24.00 0 37 1 0
#> 53.2 24.00 0 32 0 1
#> 35.2 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 64 24.00 0 43 0 0
#> 160 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 73 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 135.1 24.00 0 58 1 0
#> 62 24.00 0 71 0 0
#> 84.2 24.00 0 39 0 1
#> 54 24.00 0 53 1 0
#> 173.1 24.00 0 19 0 1
#> 200.1 24.00 0 64 0 0
#> 67.1 24.00 0 25 0 0
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 73.1 24.00 0 NA 0 1
#> 135.2 24.00 0 58 1 0
#> 138.1 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 142.3 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 182.2 24.00 0 35 0 0
#> 191 24.00 0 60 0 1
#> 53.3 24.00 0 32 0 1
#> 3 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 118 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 48 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 119.1 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 198 24.00 0 66 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.80 NA NA NA
#> 2 age, Cure model 0.0285 NA NA NA
#> 3 grade_ii, Cure model 0.737 NA NA NA
#> 4 grade_iii, Cure model 1.19 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000575 NA NA NA
#> 2 grade_ii, Survival model 0.775 NA NA NA
#> 3 grade_iii, Survival model 0.529 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.79701 0.02848 0.73676 1.18809
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 241.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.79701491 0.02847571 0.73676004 1.18809428
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0005747655 0.7754530877 0.5288412721
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.40568986 0.77156455 0.70573883 0.65989866 0.89541009 0.30126441
#> [7] 0.39515034 0.89541009 0.81281173 0.53108196 0.74274341 0.50311460
#> [13] 0.44603474 0.16164478 0.04163627 0.04163627 0.04163627 0.83862152
#> [19] 0.81281173 0.33872741 0.28569127 0.77156455 0.71320459 0.81281173
#> [25] 0.56787664 0.93723266 0.73534415 0.48420175 0.62722088 0.13629270
#> [31] 0.93723266 0.42646553 0.44603474 0.56787664 0.68303463 0.42646553
#> [37] 0.79229008 0.60193856 0.69076935 0.20390797 0.30126441 0.92538088
#> [43] 0.65989866 0.88309327 0.99443839 0.44603474 0.40568986 0.63546421
#> [49] 0.51252490 0.94897332 0.44603474 0.36201614 0.25322100 0.61048987
#> [55] 0.65186270 0.89541009 0.38425498 0.92538088 0.76447764 0.97200465
#> [61] 0.78536207 0.87056105 0.20390797 0.88309327 0.11076019 0.91937833
#> [67] 0.23695268 0.56787664 0.75730709 0.85802088 0.30126441 0.98329921
#> [73] 0.97200465 0.55872472 0.85802088 0.33872741 0.56787664 0.71320459
#> [79] 0.94897332 0.98329921 0.54946121 0.75005117 0.36201614 0.87056105
#> [85] 0.69076935 0.48420175 0.79917419 0.89541009 0.80601460 0.53108196
#> [91] 0.84514904 0.71320459 0.52180545 0.85161527 0.81281173 0.64370264
#> [97] 0.65989866 0.26946909 0.96629001 0.96053422 0.61889622 0.18426689
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 150 18 188 192 43 139 190 43.1 60 8 125 55 105
#> 20.33 15.21 16.16 16.44 12.10 21.49 20.81 12.10 13.15 18.43 15.65 19.34 19.75
#> 164 24 24.1 24.2 155 60.1 153 194 18.1 100 60.2 51 52
#> 23.60 23.89 23.89 23.89 13.08 13.15 21.33 22.40 15.21 16.07 13.15 18.23 10.42
#> 26 170 111 168 52.1 158 105.1 51.1 5 158.1 96 41 79
#> 15.77 19.54 17.45 23.72 10.42 20.14 19.75 18.23 16.43 20.14 14.54 18.02 16.23
#> 69 139.1 159 192.1 49 91 105.2 150.1 30 97 183 105.3 99
#> 23.23 21.49 10.55 16.44 12.19 5.33 19.75 20.33 17.43 19.14 9.24 19.75 21.19
#> 113 134 106 43.2 32 159.1 29 77 180 177 69.1 49.1 86
#> 22.86 17.81 16.67 12.10 20.90 10.55 15.45 7.27 14.82 12.53 23.23 12.19 23.81
#> 107 92 51.2 167 154 139.2 25 77.1 108 154.1 153.1 51.3 100.1
#> 11.18 22.92 18.23 15.55 12.63 21.49 6.32 7.27 18.29 12.63 21.33 18.23 16.07
#> 183.1 25.1 88 39 99.1 177.1 79.1 170.1 57 43.3 13 8.1 123
#> 9.24 6.32 18.37 15.59 21.19 12.53 16.23 19.54 14.46 12.10 14.34 18.43 13.00
#> 100.2 179 140 60.3 45 85 169 70 149 117 129 178 121
#> 16.07 18.63 12.68 13.15 17.42 16.44 22.41 7.38 8.37 17.46 23.41 24.00 24.00
#> 174 27 135 142 165 83 162 165.1 84 84.1 98 53 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 94 148 121.1 80 172 200 102 119 53.1 104 146 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 112.1 142.2 182 87 185 178.1 173 182.1 46 21 104.1 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 12 33 67 35.1 116 7 53.2 35.2 72 64 160 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 31 2 135.1 62 84.2 54 173.1 200.1 67.1 186 74 135.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 1 142.3 9 182.2 191 53.3 3 172.1 151 118 103 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.1 48 83.1 119.1 193 198
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[25]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006559914 0.693887327 0.801939845
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.4074720590 -0.0002224208 0.7927685247
#> grade_iii, Cure model
#> 1.0894363233
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 52 10.42 1 52 0 1
#> 8 18.43 1 32 0 0
#> 60 13.15 1 38 1 0
#> 63 22.77 1 31 1 0
#> 14 12.89 1 21 0 0
#> 29 15.45 1 68 1 0
#> 154 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 158 20.14 1 74 1 0
#> 125 15.65 1 67 1 0
#> 42 12.43 1 49 0 1
#> 105 19.75 1 60 0 0
#> 188.1 16.16 1 46 0 1
#> 18 15.21 1 49 1 0
#> 23 16.92 1 61 0 0
#> 175 21.91 1 43 0 0
#> 36 21.19 1 48 0 1
#> 129 23.41 1 53 1 0
#> 5 16.43 1 51 0 1
#> 51 18.23 1 83 0 1
#> 41 18.02 1 40 1 0
#> 68 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 66 22.13 1 53 0 0
#> 79 16.23 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 26 15.77 1 49 0 1
#> 124.1 9.73 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 60.1 13.15 1 38 1 0
#> 130 16.47 1 53 0 1
#> 114 13.68 1 NA 0 0
#> 127 3.53 1 62 0 1
#> 85 16.44 1 36 0 0
#> 40 18.00 1 28 1 0
#> 130.1 16.47 1 53 0 1
#> 140 12.68 1 59 1 0
#> 188.2 16.16 1 46 0 1
#> 166 19.98 1 48 0 0
#> 171 16.57 1 41 0 1
#> 8.1 18.43 1 32 0 0
#> 125.1 15.65 1 67 1 0
#> 66.1 22.13 1 53 0 0
#> 188.3 16.16 1 46 0 1
#> 8.2 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 52.1 10.42 1 52 0 1
#> 100 16.07 1 60 0 0
#> 170 19.54 1 43 0 1
#> 79.1 16.23 1 54 1 0
#> 190 20.81 1 42 1 0
#> 4 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 55 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 39 15.59 1 37 0 1
#> 40.1 18.00 1 28 1 0
#> 52.2 10.42 1 52 0 1
#> 15 22.68 1 48 0 0
#> 56 12.21 1 60 0 0
#> 197 21.60 1 69 1 0
#> 91 5.33 1 61 0 1
#> 16 8.71 1 71 0 1
#> 69 23.23 1 25 0 1
#> 136.1 21.83 1 43 0 1
#> 99.1 21.19 1 38 0 1
#> 125.2 15.65 1 67 1 0
#> 96 14.54 1 33 0 1
#> 77 7.27 1 67 0 1
#> 29.1 15.45 1 68 1 0
#> 43 12.10 1 61 0 1
#> 170.1 19.54 1 43 0 1
#> 90 20.94 1 50 0 1
#> 189 10.51 1 NA 1 0
#> 77.1 7.27 1 67 0 1
#> 187 9.92 1 39 1 0
#> 14.1 12.89 1 21 0 0
#> 188.4 16.16 1 46 0 1
#> 92 22.92 1 47 0 1
#> 105.1 19.75 1 60 0 0
#> 134 17.81 1 47 1 0
#> 199 19.81 1 NA 0 1
#> 175.2 21.91 1 43 0 0
#> 175.3 21.91 1 43 0 0
#> 25 6.32 1 34 1 0
#> 60.2 13.15 1 38 1 0
#> 25.1 6.32 1 34 1 0
#> 81 14.06 1 34 0 0
#> 25.2 6.32 1 34 1 0
#> 49 12.19 1 48 1 0
#> 32 20.90 1 37 1 0
#> 168 23.72 1 70 0 0
#> 63.1 22.77 1 31 1 0
#> 117.1 17.46 1 26 0 1
#> 8.3 18.43 1 32 0 0
#> 77.2 7.27 1 67 0 1
#> 4.1 17.64 1 NA 0 1
#> 29.2 15.45 1 68 1 0
#> 51.1 18.23 1 83 0 1
#> 78 23.88 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 51.2 18.23 1 83 0 1
#> 52.3 10.42 1 52 0 1
#> 106 16.67 1 49 1 0
#> 63.2 22.77 1 31 1 0
#> 36.1 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 15.1 22.68 1 48 0 0
#> 101.1 9.97 1 10 0 1
#> 16.1 8.71 1 71 0 1
#> 17 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 142 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 151 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 122 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 173 24.00 0 19 0 1
#> 165.1 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 173.1 24.00 0 19 0 1
#> 176 24.00 0 43 0 1
#> 198.1 24.00 0 66 0 1
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 147 24.00 0 76 1 0
#> 182 24.00 0 35 0 0
#> 151.1 24.00 0 42 0 0
#> 65 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 182.1 24.00 0 35 0 0
#> 148.1 24.00 0 61 1 0
#> 74 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 185.1 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 115 24.00 0 NA 1 0
#> 112.2 24.00 0 61 0 0
#> 109 24.00 0 48 0 0
#> 160.1 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 64 24.00 0 43 0 0
#> 182.2 24.00 0 35 0 0
#> 80.1 24.00 0 41 0 0
#> 120.1 24.00 0 68 0 1
#> 142.1 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 161 24.00 0 45 0 0
#> 109.1 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 48.1 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 186 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 109.2 24.00 0 48 0 0
#> 137 24.00 0 45 1 0
#> 163.1 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 33.2 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 146.1 24.00 0 63 1 0
#> 17.1 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 64.1 24.00 0 43 0 0
#> 161.1 24.00 0 45 0 0
#> 12.1 24.00 0 63 0 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 98 24.00 0 34 1 0
#> 83.1 24.00 0 6 0 0
#> 98.1 24.00 0 34 1 0
#> 84.1 24.00 0 39 0 1
#> 191 24.00 0 60 0 1
#> 72 24.00 0 40 0 1
#> 142.2 24.00 0 53 0 0
#> 182.3 24.00 0 35 0 0
#> 137.1 24.00 0 45 1 0
#> 19 24.00 0 57 0 1
#> 17.2 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.407 NA NA NA
#> 2 age, Cure model -0.000222 NA NA NA
#> 3 grade_ii, Cure model 0.793 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00656 NA NA NA
#> 2 grade_ii, Survival model 0.694 NA NA NA
#> 3 grade_iii, Survival model 0.802 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.4074721 -0.0002224 0.7927685 1.0894363
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 251.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.4074720590 -0.0002224208 0.7927685247 1.0894363233
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006559914 0.693887327 0.801939845
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.93198441 0.63777189 0.87783742 0.29593111 0.89158798 0.84921521
#> [7] 0.90531963 0.79210555 0.57768269 0.82911787 0.90984528 0.59562037
#> [13] 0.79210555 0.86360565 0.73776885 0.40545429 0.49940002 0.21420977
#> [19] 0.77474853 0.66909995 0.69057894 0.56836165 0.94870393 0.37505335
#> [25] 0.78065569 0.40545429 0.82385339 0.46136479 0.87783742 0.75675856
#> [31] 0.99621898 0.76874452 0.69769471 0.75675856 0.90076478 0.79210555
#> [37] 0.58667690 0.75052795 0.63777189 0.82911787 0.37505335 0.79210555
#> [43] 0.63777189 0.72491463 0.93198441 0.81851816 0.61312149 0.78065569
#> [49] 0.55898918 0.71826397 0.62969700 0.49940002 0.84420963 0.69769471
#> [55] 0.93198441 0.34359425 0.91432470 0.48707728 0.99240394 0.96112781
#> [61] 0.24676452 0.46136479 0.49940002 0.82911787 0.86838239 0.96919039
#> [67] 0.84921521 0.92322486 0.61312149 0.53944588 0.96919039 0.95699945
#> [73] 0.89158798 0.79210555 0.27357497 0.59562037 0.71146116 0.40545429
#> [79] 0.40545429 0.98090027 0.87783742 0.98090027 0.87311310 0.98090027
#> [85] 0.91879355 0.54935232 0.16915299 0.29593111 0.72491463 0.63777189
#> [91] 0.96919039 0.84921521 0.66909995 0.07956605 0.07956605 0.66909995
#> [97] 0.93198441 0.74419653 0.29593111 0.49940002 0.92760722 0.34359425
#> [103] 0.94870393 0.96112781 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 52 8 60 63 14 29 154 188 158 125 42 105 188.1
#> 10.42 18.43 13.15 22.77 12.89 15.45 12.63 16.16 20.14 15.65 12.43 19.75 16.16
#> 18 23 175 36 129 5 51 41 68 101 66 79 175.1
#> 15.21 16.92 21.91 21.19 23.41 16.43 18.23 18.02 20.62 9.97 22.13 16.23 21.91
#> 26 136 60.1 130 127 85 40 130.1 140 188.2 166 171 8.1
#> 15.77 21.83 13.15 16.47 3.53 16.44 18.00 16.47 12.68 16.16 19.98 16.57 18.43
#> 125.1 66.1 188.3 8.2 117 52.1 100 170 79.1 190 110 55 99
#> 15.65 22.13 16.16 18.43 17.46 10.42 16.07 19.54 16.23 20.81 17.56 19.34 21.19
#> 39 40.1 52.2 15 56 197 91 16 69 136.1 99.1 125.2 96
#> 15.59 18.00 10.42 22.68 12.21 21.60 5.33 8.71 23.23 21.83 21.19 15.65 14.54
#> 77 29.1 43 170.1 90 77.1 187 14.1 188.4 92 105.1 134 175.2
#> 7.27 15.45 12.10 19.54 20.94 7.27 9.92 12.89 16.16 22.92 19.75 17.81 21.91
#> 175.3 25 60.2 25.1 81 25.2 49 32 168 63.1 117.1 8.3 77.2
#> 21.91 6.32 13.15 6.32 14.06 6.32 12.19 20.90 23.72 22.77 17.46 18.43 7.27
#> 29.2 51.1 78 78.1 51.2 52.3 106 63.2 36.1 10 15.1 101.1 16.1
#> 15.45 18.23 23.88 23.88 18.23 10.42 16.67 22.77 21.19 10.53 22.68 9.97 8.71
#> 17 84 142 53 160 112 151 198 122 165 173 165.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 119 173.1 176 198.1 102 185 148 147 182 151.1 65 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 112.1 120 182.1 148.1 74 80 95 185.1 33 35 176.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 48 172 112.2 109 160.1 126 94 64 182.2 80.1 120.1 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 161 109.1 31 48.1 53.1 186 71 109.2 137 163.1 193 33.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 146.1 17.1 44 64.1 161.1 12.1 22 83 98 83.1 98.1 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 72 142.2 182.3 137.1 19 17.2 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[26]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0005671027 0.4343505838 0.1468041202
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.269511631 -0.005471291 -0.130670367
#> grade_iii, Cure model
#> 0.712346868
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 76 19.22 1 54 0 1
#> 170 19.54 1 43 0 1
#> 58 19.34 1 39 0 0
#> 40 18.00 1 28 1 0
#> 123 13.00 1 44 1 0
#> 39 15.59 1 37 0 1
#> 184 17.77 1 38 0 0
#> 194 22.40 1 38 0 1
#> 130 16.47 1 53 0 1
#> 92 22.92 1 47 0 1
#> 110 17.56 1 65 0 1
#> 13 14.34 1 54 0 1
#> 99 21.19 1 38 0 1
#> 86 23.81 1 58 0 1
#> 10 10.53 1 34 0 0
#> 140 12.68 1 59 1 0
#> 69 23.23 1 25 0 1
#> 183 9.24 1 67 1 0
#> 168 23.72 1 70 0 0
#> 5 16.43 1 51 0 1
#> 88.1 18.37 1 47 0 0
#> 100 16.07 1 60 0 0
#> 56 12.21 1 60 0 0
#> 69.1 23.23 1 25 0 1
#> 197 21.60 1 69 1 0
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 195 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 167 15.55 1 56 1 0
#> 157 15.10 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 24 23.89 1 38 0 0
#> 157.2 15.10 1 47 0 0
#> 51 18.23 1 83 0 1
#> 6 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 78 23.88 1 43 0 0
#> 8.1 18.43 1 32 0 0
#> 58.1 19.34 1 39 0 0
#> 25 6.32 1 34 1 0
#> 86.1 23.81 1 58 0 1
#> 15 22.68 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 170.1 19.54 1 43 0 1
#> 76.1 19.22 1 54 0 1
#> 92.1 22.92 1 47 0 1
#> 85 16.44 1 36 0 0
#> 155 13.08 1 26 0 0
#> 42 12.43 1 49 0 1
#> 183.1 9.24 1 67 1 0
#> 39.1 15.59 1 37 0 1
#> 110.1 17.56 1 65 0 1
#> 24.1 23.89 1 38 0 0
#> 63 22.77 1 31 1 0
#> 10.1 10.53 1 34 0 0
#> 166 19.98 1 48 0 0
#> 41.1 18.02 1 40 1 0
#> 175 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 105 19.75 1 60 0 0
#> 180 14.82 1 37 0 0
#> 15.1 22.68 1 48 0 0
#> 81 14.06 1 34 0 0
#> 57 14.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 180.1 14.82 1 37 0 0
#> 130.1 16.47 1 53 0 1
#> 113 22.86 1 34 0 0
#> 8.2 18.43 1 32 0 0
#> 105.1 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 86.2 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 76.2 19.22 1 54 0 1
#> 91 5.33 1 61 0 1
#> 140.1 12.68 1 59 1 0
#> 5.1 16.43 1 51 0 1
#> 129 23.41 1 53 1 0
#> 37 12.52 1 57 1 0
#> 63.1 22.77 1 31 1 0
#> 78.1 23.88 1 43 0 0
#> 190 20.81 1 42 1 0
#> 85.1 16.44 1 36 0 0
#> 5.2 16.43 1 51 0 1
#> 69.2 23.23 1 25 0 1
#> 171 16.57 1 41 0 1
#> 180.2 14.82 1 37 0 0
#> 51.1 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 199.1 19.81 1 NA 0 1
#> 145 10.07 1 65 1 0
#> 101 9.97 1 10 0 1
#> 187 9.92 1 39 1 0
#> 37.1 12.52 1 57 1 0
#> 155.1 13.08 1 26 0 0
#> 42.1 12.43 1 49 0 1
#> 76.3 19.22 1 54 0 1
#> 8.3 18.43 1 32 0 0
#> 15.2 22.68 1 48 0 0
#> 117 17.46 1 26 0 1
#> 171.1 16.57 1 41 0 1
#> 129.1 23.41 1 53 1 0
#> 195.1 11.76 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 61 10.12 1 36 0 1
#> 169 22.41 1 46 0 0
#> 164 23.60 1 76 0 1
#> 175.1 21.91 1 43 0 0
#> 90 20.94 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 102 24.00 0 49 0 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 116.1 24.00 0 58 0 1
#> 182 24.00 0 35 0 0
#> 156 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 200 24.00 0 64 0 0
#> 21 24.00 0 47 0 0
#> 182.1 24.00 0 35 0 0
#> 109 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 156.1 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 72 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 94 24.00 0 51 0 1
#> 165 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 12 24.00 0 63 0 0
#> 28.1 24.00 0 67 1 0
#> 148 24.00 0 61 1 0
#> 198 24.00 0 66 0 1
#> 115 24.00 0 NA 1 0
#> 163 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 193 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 182.2 24.00 0 35 0 0
#> 119 24.00 0 17 0 0
#> 22 24.00 0 52 1 0
#> 38.1 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 54 24.00 0 53 1 0
#> 165.1 24.00 0 47 0 0
#> 152 24.00 0 36 0 1
#> 148.1 24.00 0 61 1 0
#> 176 24.00 0 43 0 1
#> 74 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 182.3 24.00 0 35 0 0
#> 191 24.00 0 60 0 1
#> 132.1 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 198.1 24.00 0 66 0 1
#> 46 24.00 0 71 0 0
#> 165.2 24.00 0 47 0 0
#> 22.1 24.00 0 52 1 0
#> 22.2 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 115.1 24.00 0 NA 1 0
#> 19.1 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 7.1 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 138 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 119.1 24.00 0 17 0 0
#> 126.1 24.00 0 48 0 0
#> 161.1 24.00 0 45 0 0
#> 141 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 193.1 24.00 0 45 0 1
#> 65 24.00 0 57 1 0
#> 176.1 24.00 0 43 0 1
#> 156.2 24.00 0 50 1 0
#> 7.2 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 94.2 24.00 0 51 0 1
#> 38.2 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.270 NA NA NA
#> 2 age, Cure model -0.00547 NA NA NA
#> 3 grade_ii, Cure model -0.131 NA NA NA
#> 4 grade_iii, Cure model 0.712 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000567 NA NA NA
#> 2 grade_ii, Survival model 0.434 NA NA NA
#> 3 grade_iii, Survival model 0.147 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.269512 -0.005471 -0.130670 0.712347
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 258 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.269511631 -0.005471291 -0.130670367 0.712346868
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0005671027 0.4343505838 0.1468041202
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.49062178 0.40923582 0.37195448 0.39058534 0.54532434 0.83263184
#> [7] 0.70338777 0.56324571 0.26573734 0.61624741 0.17579474 0.57217296
#> [13] 0.79815919 0.31496117 0.06509119 0.90861296 0.84122859 0.14532948
#> [19] 0.96718312 0.09833492 0.65999065 0.49062178 0.68588980 0.90020048
#> [25] 0.14532948 0.29541976 0.78084710 0.52732549 0.45457282 0.72072187
#> [31] 0.72938968 0.72938968 0.01404672 0.72938968 0.50900829 0.69463758
#> [37] 0.30526702 0.03902385 0.45457282 0.39058534 0.98359644 0.06509119
#> [43] 0.22671969 0.37195448 0.40923582 0.17579474 0.64252338 0.81543775
#> [49] 0.88345936 0.96718312 0.70338777 0.57217296 0.01404672 0.20704678
#> [55] 0.90861296 0.34371437 0.52732549 0.27574100 0.85816443 0.35320153
#> [61] 0.75510925 0.22671969 0.80679759 0.78950927 0.44529349 0.75510925
#> [67] 0.61624741 0.19643121 0.45457282 0.35320153 0.06509119 0.92536592
#> [73] 0.40923582 0.99180224 0.84122859 0.65999065 0.12358169 0.86667806
#> [79] 0.20704678 0.03902385 0.33423426 0.64252338 0.65999065 0.14532948
#> [85] 0.59869875 0.75510925 0.50900829 0.55432148 0.94216620 0.95052489
#> [91] 0.95887246 0.86667806 0.81543775 0.88345936 0.40923582 0.45457282
#> [97] 0.22671969 0.58982472 0.59869875 0.12358169 0.63373445 0.93377115
#> [103] 0.25568322 0.11103585 0.27574100 0.32461569 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 88 76 170 58 40 123 39 184 194 130 92 110 13
#> 18.37 19.22 19.54 19.34 18.00 13.00 15.59 17.77 22.40 16.47 22.92 17.56 14.34
#> 99 86 10 140 69 183 168 5 88.1 100 56 69.1 197
#> 21.19 23.81 10.53 12.68 23.23 9.24 23.72 16.43 18.37 16.07 12.21 23.23 21.60
#> 96 41 8 167 157 157.1 24 157.2 51 6 139 78 8.1
#> 14.54 18.02 18.43 15.55 15.10 15.10 23.89 15.10 18.23 15.64 21.49 23.88 18.43
#> 58.1 25 86.1 15 170.1 76.1 92.1 85 155 42 183.1 39.1 110.1
#> 19.34 6.32 23.81 22.68 19.54 19.22 22.92 16.44 13.08 12.43 9.24 15.59 17.56
#> 24.1 63 10.1 166 41.1 175 177 105 180 15.1 81 57 97
#> 23.89 22.77 10.53 19.98 18.02 21.91 12.53 19.75 14.82 22.68 14.06 14.46 19.14
#> 180.1 130.1 113 8.2 105.1 86.2 93 76.2 91 140.1 5.1 129 37
#> 14.82 16.47 22.86 18.43 19.75 23.81 10.33 19.22 5.33 12.68 16.43 23.41 12.52
#> 63.1 78.1 190 85.1 5.2 69.2 171 180.2 51.1 134 145 101 187
#> 22.77 23.88 20.81 16.44 16.43 23.23 16.57 14.82 18.23 17.81 10.07 9.97 9.92
#> 37.1 155.1 42.1 76.3 8.3 15.2 117 171.1 129.1 181 61 169 164
#> 12.52 13.08 12.43 19.22 18.43 22.68 17.46 16.57 23.41 16.46 10.12 22.41 23.60
#> 175.1 90 102 104 143 19 116 116.1 182 156 28 200 21
#> 21.91 20.94 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 109 161 112 156.1 160 34 72 44 94 165 38 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 28.1 148 198 163 162 80 11 193 146 2 172 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.2 119 22 38.1 94.1 54 165.1 152 148.1 176 74 12.1 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 182.3 191 132.1 126 198.1 46 165.2 22.1 22.2 7 19.1 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 71 64 138 178 119.1 126.1 161.1 141 112.1 3 109.1 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 65 176.1 156.2 7.2 142 35 94.2 38.2 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[27]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007508305 0.148598714 0.481452763
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.395304150 0.006867184 0.158813802
#> grade_iii, Cure model
#> 0.621395924
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 10 10.53 1 34 0 0
#> 68 20.62 1 44 0 0
#> 166 19.98 1 48 0 0
#> 14 12.89 1 21 0 0
#> 5 16.43 1 51 0 1
#> 105 19.75 1 60 0 0
#> 18 15.21 1 49 1 0
#> 166.1 19.98 1 48 0 0
#> 42 12.43 1 49 0 1
#> 157 15.10 1 47 0 0
#> 18.1 15.21 1 49 1 0
#> 180 14.82 1 37 0 0
#> 26 15.77 1 49 0 1
#> 100 16.07 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 57 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 180.1 14.82 1 37 0 0
#> 158 20.14 1 74 1 0
#> 16 8.71 1 71 0 1
#> 85 16.44 1 36 0 0
#> 60 13.15 1 38 1 0
#> 37 12.52 1 57 1 0
#> 192 16.44 1 31 1 0
#> 159 10.55 1 50 0 1
#> 140 12.68 1 59 1 0
#> 167 15.55 1 56 1 0
#> 40 18.00 1 28 1 0
#> 136 21.83 1 43 0 1
#> 36 21.19 1 48 0 1
#> 51 18.23 1 83 0 1
#> 40.1 18.00 1 28 1 0
#> 190.1 20.81 1 42 1 0
#> 61 10.12 1 36 0 1
#> 153 21.33 1 55 1 0
#> 127 3.53 1 62 0 1
#> 49 12.19 1 48 1 0
#> 59 10.16 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 110 17.56 1 65 0 1
#> 106 16.67 1 49 1 0
#> 10.1 10.53 1 34 0 0
#> 140.1 12.68 1 59 1 0
#> 149 8.37 1 33 1 0
#> 77 7.27 1 67 0 1
#> 159.1 10.55 1 50 0 1
#> 37.1 12.52 1 57 1 0
#> 50 10.02 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 153.1 21.33 1 55 1 0
#> 68.1 20.62 1 44 0 0
#> 190.2 20.81 1 42 1 0
#> 24 23.89 1 38 0 0
#> 180.2 14.82 1 37 0 0
#> 159.2 10.55 1 50 0 1
#> 79 16.23 1 54 1 0
#> 155 13.08 1 26 0 0
#> 76 19.22 1 54 0 1
#> 110.1 17.56 1 65 0 1
#> 127.1 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 24.1 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 175.1 21.91 1 43 0 0
#> 4.1 17.64 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 130 16.47 1 53 0 1
#> 149.1 8.37 1 33 1 0
#> 4.2 17.64 1 NA 0 1
#> 42.1 12.43 1 49 0 1
#> 125 15.65 1 67 1 0
#> 43 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 199 19.81 1 NA 0 1
#> 39 15.59 1 37 0 1
#> 105.1 19.75 1 60 0 0
#> 136.1 21.83 1 43 0 1
#> 56 12.21 1 60 0 0
#> 179 18.63 1 42 0 0
#> 89 11.44 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 129.1 23.41 1 53 1 0
#> 195 11.76 1 NA 1 0
#> 157.1 15.10 1 47 0 0
#> 194 22.40 1 38 0 1
#> 105.2 19.75 1 60 0 0
#> 60.1 13.15 1 38 1 0
#> 5.1 16.43 1 51 0 1
#> 150.1 20.33 1 48 0 0
#> 25 6.32 1 34 1 0
#> 114 13.68 1 NA 0 0
#> 149.2 8.37 1 33 1 0
#> 77.1 7.27 1 67 0 1
#> 49.1 12.19 1 48 1 0
#> 192.1 16.44 1 31 1 0
#> 110.2 17.56 1 65 0 1
#> 194.1 22.40 1 38 0 1
#> 40.2 18.00 1 28 1 0
#> 16.1 8.71 1 71 0 1
#> 188 16.16 1 46 0 1
#> 77.2 7.27 1 67 0 1
#> 188.1 16.16 1 46 0 1
#> 127.2 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 155.1 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 25.1 6.32 1 34 1 0
#> 195.1 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 139.1 21.49 1 63 1 0
#> 119 24.00 0 17 0 0
#> 9 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 119.1 24.00 0 17 0 0
#> 33 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 67 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 172 24.00 0 41 0 0
#> 174 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 172.1 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 138.1 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 193 24.00 0 45 0 1
#> 185 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 47 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 176 24.00 0 43 0 1
#> 193.1 24.00 0 45 0 1
#> 198 24.00 0 66 0 1
#> 27 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 7 24.00 0 37 1 0
#> 135 24.00 0 58 1 0
#> 53 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 137.1 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 47.1 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 102 24.00 0 49 0 0
#> 35 24.00 0 51 0 0
#> 7.1 24.00 0 37 1 0
#> 28 24.00 0 67 1 0
#> 200.1 24.00 0 64 0 0
#> 67.1 24.00 0 25 0 0
#> 160 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 87 24.00 0 27 0 0
#> 151 24.00 0 42 0 0
#> 3 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 95.1 24.00 0 68 0 1
#> 138.2 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 119.2 24.00 0 17 0 0
#> 122.1 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 19 24.00 0 57 0 1
#> 9.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 120 24.00 0 68 0 1
#> 112.1 24.00 0 61 0 0
#> 185.1 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 132 24.00 0 55 0 0
#> 116 24.00 0 58 0 1
#> 9.2 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 27.1 24.00 0 63 1 0
#> 131 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 54 24.00 0 53 1 0
#> 131.1 24.00 0 66 0 0
#> 27.2 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 19.2 24.00 0 57 0 1
#> 82.1 24.00 0 34 0 0
#> 11.1 24.00 0 42 0 1
#> 7.2 24.00 0 37 1 0
#> 196.1 24.00 0 19 0 0
#> 95.2 24.00 0 68 0 1
#> 67.2 24.00 0 25 0 0
#> 121 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.395 NA NA NA
#> 2 age, Cure model 0.00687 NA NA NA
#> 3 grade_ii, Cure model 0.159 NA NA NA
#> 4 grade_iii, Cure model 0.621 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00751 NA NA NA
#> 2 grade_ii, Survival model 0.149 NA NA NA
#> 3 grade_iii, Survival model 0.481 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.395304 0.006867 0.158814 0.621396
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 255.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.395304150 0.006867184 0.158813802 0.621395924
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007508305 0.148598714 0.481452763
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.49862752 0.90014400 0.39325238 0.44805779 0.80666890 0.63013334
#> [7] 0.46887086 0.71901176 0.44805779 0.84536762 0.73285772 0.71901176
#> [13] 0.74659387 0.67578975 0.66832828 0.41553349 0.76692423 0.35957334
#> [19] 0.74659387 0.43730837 0.92936188 0.60618930 0.78036307 0.83265340
#> [25] 0.60618930 0.88245723 0.81325136 0.70484832 0.53753114 0.25117016
#> [31] 0.33474187 0.52816866 0.53753114 0.35957334 0.92359524 0.30889010
#> [37] 0.98428488 0.86405967 0.77368531 0.56453415 0.58957727 0.90014400
#> [43] 0.81325136 0.94061465 0.95729803 0.88245723 0.83265340 0.12843409
#> [49] 0.30889010 0.39325238 0.35957334 0.06056026 0.74659387 0.88245723
#> [55] 0.64565536 0.79353948 0.50868110 0.56453415 0.98428488 0.21581375
#> [61] 0.06056026 0.91192909 0.21581375 0.91778796 0.59796458 0.94061465
#> [67] 0.84536762 0.68314259 0.87635487 0.28130128 0.69767825 0.46887086
#> [73] 0.25117016 0.85783101 0.51845882 0.71196290 0.12843409 0.73285772
#> [79] 0.17812511 0.46887086 0.78036307 0.63013334 0.41553349 0.97350783
#> [85] 0.94061465 0.95729803 0.86405967 0.60618930 0.56453415 0.17812511
#> [91] 0.53753114 0.92936188 0.65339430 0.95729803 0.65339430 0.98428488
#> [97] 0.69042343 0.79353948 0.34727558 0.97350783 0.82619463 0.28130128
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 58 10 68 166 14 5 105 18 166.1 42 157 18.1 180
#> 19.34 10.53 20.62 19.98 12.89 16.43 19.75 15.21 19.98 12.43 15.10 15.21 14.82
#> 26 100 150 57 190 180.1 158 16 85 60 37 192 159
#> 15.77 16.07 20.33 14.46 20.81 14.82 20.14 8.71 16.44 13.15 12.52 16.44 10.55
#> 140 167 40 136 36 51 40.1 190.1 61 153 127 49 13
#> 12.68 15.55 18.00 21.83 21.19 18.23 18.00 20.81 10.12 21.33 3.53 12.19 14.34
#> 110 106 10.1 140.1 149 77 159.1 37.1 129 153.1 68.1 190.2 24
#> 17.56 16.67 10.53 12.68 8.37 7.27 10.55 12.52 23.41 21.33 20.62 20.81 23.89
#> 180.2 159.2 79 155 76 110.1 127.1 175 24.1 52 175.1 93 130
#> 14.82 10.55 16.23 13.08 19.22 17.56 3.53 21.91 23.89 10.42 21.91 10.33 16.47
#> 149.1 42.1 125 43 139 39 105.1 136.1 56 179 29 129.1 157.1
#> 8.37 12.43 15.65 12.10 21.49 15.59 19.75 21.83 12.21 18.63 15.45 23.41 15.10
#> 194 105.2 60.1 5.1 150.1 25 149.2 77.1 49.1 192.1 110.2 194.1 40.2
#> 22.40 19.75 13.15 16.43 20.33 6.32 8.37 7.27 12.19 16.44 17.56 22.40 18.00
#> 16.1 188 77.2 188.1 127.2 6 155.1 32 25.1 177 139.1 119 9
#> 8.71 16.16 7.27 16.16 3.53 15.64 13.08 20.90 6.32 12.53 21.49 24.00 24.00
#> 34 178 137 119.1 33 64 67 148 172 174 138 142 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 65 138.1 65.1 193 185 200 47 95 12 112 176 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 27 7 135 53 17 156 137.1 22 47.1 102 35 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 200.1 67.1 160 146 84 87 151 3 122 95.1 138.2 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.2 122.1 80 196 19 9.1 82 120 112.1 185.1 103 132 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 19.1 27.1 131 161 161.1 54 131.1 27.2 152 1 19.2 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 7.2 196.1 95.2 67.2 121
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[28]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001657558 0.856121888 0.376665181
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.59812796 0.00800593 0.26411619
#> grade_iii, Cure model
#> 0.94762767
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 113 22.86 1 34 0 0
#> 97 19.14 1 65 0 1
#> 190 20.81 1 42 1 0
#> 192 16.44 1 31 1 0
#> 10 10.53 1 34 0 0
#> 194 22.40 1 38 0 1
#> 171 16.57 1 41 0 1
#> 36 21.19 1 48 0 1
#> 61 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 51 18.23 1 83 0 1
#> 183 9.24 1 67 1 0
#> 45 17.42 1 54 0 1
#> 177 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 110 17.56 1 65 0 1
#> 145 10.07 1 65 1 0
#> 105 19.75 1 60 0 0
#> 183.1 9.24 1 67 1 0
#> 86 23.81 1 58 0 1
#> 42 12.43 1 49 0 1
#> 6 15.64 1 39 0 0
#> 56 12.21 1 60 0 0
#> 128 20.35 1 35 0 1
#> 194.1 22.40 1 38 0 1
#> 51.1 18.23 1 83 0 1
#> 6.1 15.64 1 39 0 0
#> 180 14.82 1 37 0 0
#> 93 10.33 1 52 0 1
#> 170 19.54 1 43 0 1
#> 159 10.55 1 50 0 1
#> 63 22.77 1 31 1 0
#> 43 12.10 1 61 0 1
#> 168 23.72 1 70 0 0
#> 37 12.52 1 57 1 0
#> 24 23.89 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 134 17.81 1 47 1 0
#> 96 14.54 1 33 0 1
#> 13 14.34 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 192.1 16.44 1 31 1 0
#> 76 19.22 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 41 18.02 1 40 1 0
#> 194.2 22.40 1 38 0 1
#> 37.1 12.52 1 57 1 0
#> 89 11.44 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 29 15.45 1 68 1 0
#> 101 9.97 1 10 0 1
#> 96.1 14.54 1 33 0 1
#> 101.1 9.97 1 10 0 1
#> 197 21.60 1 69 1 0
#> 8 18.43 1 32 0 0
#> 145.1 10.07 1 65 1 0
#> 150 20.33 1 48 0 0
#> 181 16.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 155 13.08 1 26 0 0
#> 10.1 10.53 1 34 0 0
#> 78 23.88 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 39 15.59 1 37 0 1
#> 108.1 18.29 1 39 0 1
#> 68 20.62 1 44 0 0
#> 110.1 17.56 1 65 0 1
#> 86.1 23.81 1 58 0 1
#> 29.1 15.45 1 68 1 0
#> 4 17.64 1 NA 0 1
#> 52 10.42 1 52 0 1
#> 14 12.89 1 21 0 0
#> 167.1 15.55 1 56 1 0
#> 181.1 16.46 1 45 0 1
#> 23.1 16.92 1 61 0 0
#> 77 7.27 1 67 0 1
#> 58 19.34 1 39 0 0
#> 57 14.46 1 45 0 1
#> 175.1 21.91 1 43 0 0
#> 145.2 10.07 1 65 1 0
#> 111 17.45 1 47 0 1
#> 97.1 19.14 1 65 0 1
#> 145.3 10.07 1 65 1 0
#> 55 19.34 1 69 0 1
#> 24.1 23.89 1 38 0 0
#> 164 23.60 1 76 0 1
#> 15 22.68 1 48 0 0
#> 166 19.98 1 48 0 0
#> 171.1 16.57 1 41 0 1
#> 124 9.73 1 NA 1 0
#> 197.1 21.60 1 69 1 0
#> 189 10.51 1 NA 1 0
#> 56.1 12.21 1 60 0 0
#> 187 9.92 1 39 1 0
#> 49 12.19 1 48 1 0
#> 107 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 59.1 10.16 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 125 15.65 1 67 1 0
#> 57.1 14.46 1 45 0 1
#> 23.2 16.92 1 61 0 0
#> 113.1 22.86 1 34 0 0
#> 70 7.38 1 30 1 0
#> 90.1 20.94 1 50 0 1
#> 166.1 19.98 1 48 0 0
#> 134.1 17.81 1 47 1 0
#> 45.1 17.42 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 123 13.00 1 44 1 0
#> 193 24.00 0 45 0 1
#> 126 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 151 24.00 0 42 0 0
#> 33 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 73 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 146 24.00 0 63 1 0
#> 160 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 162 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 144 24.00 0 28 0 1
#> 33.1 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 161 24.00 0 45 0 0
#> 121 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 94.1 24.00 0 51 0 1
#> 2.1 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 146.1 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 102 24.00 0 49 0 0
#> 65.1 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 120 24.00 0 68 0 1
#> 142 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 19 24.00 0 57 0 1
#> 163 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 142.1 24.00 0 53 0 0
#> 176.1 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 152.1 24.00 0 36 0 1
#> 120.1 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 102.1 24.00 0 49 0 0
#> 94.2 24.00 0 51 0 1
#> 9 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 163.1 24.00 0 66 0 0
#> 160.1 24.00 0 31 1 0
#> 163.2 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 143 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 174.1 24.00 0 49 1 0
#> 48 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 33.2 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 151.1 24.00 0 42 0 0
#> 44 24.00 0 56 0 0
#> 34.2 24.00 0 36 0 0
#> 9.1 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 65.2 24.00 0 57 1 0
#> 94.3 24.00 0 51 0 1
#> 17 24.00 0 38 0 1
#> 131.1 24.00 0 66 0 0
#> 65.3 24.00 0 57 1 0
#> 28.1 24.00 0 67 1 0
#> 28.2 24.00 0 67 1 0
#> 1 24.00 0 23 1 0
#> 172 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 1.1 24.00 0 23 1 0
#> 34.3 24.00 0 36 0 0
#> 20 24.00 0 46 1 0
#> 119 24.00 0 17 0 0
#> 73.1 24.00 0 NA 0 1
#> 143.1 24.00 0 51 0 0
#> 146.2 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 83 24.00 0 6 0 0
#> 17.1 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.598 NA NA NA
#> 2 age, Cure model 0.00801 NA NA NA
#> 3 grade_ii, Cure model 0.264 NA NA NA
#> 4 grade_iii, Cure model 0.948 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00166 NA NA NA
#> 2 grade_ii, Survival model 0.856 NA NA NA
#> 3 grade_iii, Survival model 0.377 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.598128 0.008006 0.264116 0.947628
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 253.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.59812796 0.00800593 0.26411619 0.94762767
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001657558 0.856121888 0.376665181
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.19820018 0.50898235 0.38982043 0.70179379 0.90553663 0.27301745
#> [7] 0.67063754 0.35746742 0.93031339 0.18061712 0.55503124 0.97734792
#> [13] 0.63099608 0.84165170 0.31006554 0.60652876 0.93646514 0.45070893
#> [19] 0.97734792 0.10385366 0.86114757 0.72418955 0.86758082 0.41044052
#> [25] 0.27301745 0.55503124 0.72418955 0.77423910 0.92413930 0.46078159
#> [31] 0.89930818 0.23149352 0.88673103 0.14186209 0.84827348 0.02972261
#> [37] 0.53685873 0.58156557 0.78115487 0.80830393 0.70179379 0.49940968
#> [43] 0.23149352 0.57281239 0.27301745 0.84827348 0.36860940 0.64694893
#> [49] 0.76046158 0.95984430 0.78115487 0.95984430 0.33513479 0.52751737
#> [55] 0.93646514 0.42060170 0.68631648 0.74626355 0.82167961 0.90553663
#> [61] 0.07600989 0.73890785 0.53685873 0.40014051 0.60652876 0.10385366
#> [67] 0.76046158 0.91794083 0.83502302 0.74626355 0.68631648 0.64694893
#> [73] 0.99436787 0.48023165 0.79479550 0.31006554 0.93646514 0.62284544
#> [79] 0.50898235 0.93646514 0.48023165 0.02972261 0.16199305 0.25896172
#> [85] 0.43074261 0.67063754 0.33513479 0.86758082 0.97153692 0.88037985
#> [91] 0.89305446 0.59817379 0.46078159 0.71678253 0.79479550 0.64694893
#> [97] 0.19820018 0.98871563 0.36860940 0.43074261 0.58156557 0.63099608
#> [103] 0.80830393 0.82839248 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 113 97 190 192 10 194 171 36 61 92 51 183 45
#> 22.86 19.14 20.81 16.44 10.53 22.40 16.57 21.19 10.12 22.92 18.23 9.24 17.42
#> 177 175 110 145 105 183.1 86 42 6 56 128 194.1 51.1
#> 12.53 21.91 17.56 10.07 19.75 9.24 23.81 12.43 15.64 12.21 20.35 22.40 18.23
#> 6.1 180 93 170 159 63 43 168 37 24 108 134 96
#> 15.64 14.82 10.33 19.54 10.55 22.77 12.10 23.72 12.52 23.89 18.29 17.81 14.54
#> 13 192.1 76 63.1 41 194.2 37.1 90 23 29 101 96.1 101.1
#> 14.34 16.44 19.22 22.77 18.02 22.40 12.52 20.94 16.92 15.45 9.97 14.54 9.97
#> 197 8 145.1 150 181 167 155 10.1 78 39 108.1 68 110.1
#> 21.60 18.43 10.07 20.33 16.46 15.55 13.08 10.53 23.88 15.59 18.29 20.62 17.56
#> 86.1 29.1 52 14 167.1 181.1 23.1 77 58 57 175.1 145.2 111
#> 23.81 15.45 10.42 12.89 15.55 16.46 16.92 7.27 19.34 14.46 21.91 10.07 17.45
#> 97.1 145.3 55 24.1 164 15 166 171.1 197.1 56.1 187 49 107
#> 19.14 10.07 19.34 23.89 23.60 22.68 19.98 16.57 21.60 12.21 9.92 12.19 11.18
#> 184 170.1 125 57.1 23.2 113.1 70 90.1 166.1 134.1 45.1 13.1 123
#> 17.77 19.54 15.65 14.46 16.92 22.86 7.38 20.94 19.98 17.81 17.42 14.34 13.00
#> 193 126 87 151 33 131 84 2 146 160 72 116 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 144 33.1 65 161 121 152 94.1 2.1 176 146.1 174 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 198 120 142 35 34 19 163 47 142.1 176.1 82 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 196 102.1 94.2 9 165 163.1 160.1 163.2 112 143 47.1 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 34.1 33.2 28 151.1 44 34.2 9.1 156 65.2 94.3 17 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.3 28.1 28.2 1 172 21 12 1.1 34.3 20 119 143.1 146.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 27 132 137 103 83 17.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[29]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003318716 0.228517960 0.177714904
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.307595217 0.002947016 0.133493417
#> grade_iii, Cure model
#> 0.986930096
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 123 13.00 1 44 1 0
#> 180 14.82 1 37 0 0
#> 155 13.08 1 26 0 0
#> 106 16.67 1 49 1 0
#> 41 18.02 1 40 1 0
#> 155.1 13.08 1 26 0 0
#> 29 15.45 1 68 1 0
#> 13 14.34 1 54 0 1
#> 26 15.77 1 49 0 1
#> 164 23.60 1 76 0 1
#> 6 15.64 1 39 0 0
#> 77 7.27 1 67 0 1
#> 157 15.10 1 47 0 0
#> 85 16.44 1 36 0 0
#> 99 21.19 1 38 0 1
#> 57 14.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 128 20.35 1 35 0 1
#> 13.1 14.34 1 54 0 1
#> 129 23.41 1 53 1 0
#> 23 16.92 1 61 0 0
#> 63 22.77 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 159 10.55 1 50 0 1
#> 90 20.94 1 50 0 1
#> 29.1 15.45 1 68 1 0
#> 177 12.53 1 75 0 0
#> 123.1 13.00 1 44 1 0
#> 79 16.23 1 54 1 0
#> 40 18.00 1 28 1 0
#> 5 16.43 1 51 0 1
#> 190 20.81 1 42 1 0
#> 42 12.43 1 49 0 1
#> 25 6.32 1 34 1 0
#> 4 17.64 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 175 21.91 1 43 0 0
#> 92 22.92 1 47 0 1
#> 4.1 17.64 1 NA 0 1
#> 40.1 18.00 1 28 1 0
#> 61 10.12 1 36 0 1
#> 180.1 14.82 1 37 0 0
#> 170 19.54 1 43 0 1
#> 63.1 22.77 1 31 1 0
#> 16 8.71 1 71 0 1
#> 37 12.52 1 57 1 0
#> 51 18.23 1 83 0 1
#> 153 21.33 1 55 1 0
#> 99.1 21.19 1 38 0 1
#> 14 12.89 1 21 0 0
#> 43 12.10 1 61 0 1
#> 166 19.98 1 48 0 0
#> 26.2 15.77 1 49 0 1
#> 101 9.97 1 10 0 1
#> 43.1 12.10 1 61 0 1
#> 145 10.07 1 65 1 0
#> 77.1 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 39 15.59 1 37 0 1
#> 105 19.75 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 81 14.06 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 49 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 90.1 20.94 1 50 0 1
#> 42.1 12.43 1 49 0 1
#> 29.2 15.45 1 68 1 0
#> 189 10.51 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 134.1 17.81 1 47 1 0
#> 128.1 20.35 1 35 0 1
#> 188 16.16 1 46 0 1
#> 88 18.37 1 47 0 0
#> 5.1 16.43 1 51 0 1
#> 70 7.38 1 30 1 0
#> 81.1 14.06 1 34 0 0
#> 157.1 15.10 1 47 0 0
#> 111 17.45 1 47 0 1
#> 79.1 16.23 1 54 1 0
#> 125 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 40.2 18.00 1 28 1 0
#> 168 23.72 1 70 0 0
#> 37.1 12.52 1 57 1 0
#> 89 11.44 1 NA 0 0
#> 177.1 12.53 1 75 0 0
#> 24 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 59.1 10.16 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 171 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 24.1 23.89 1 38 0 0
#> 10 10.53 1 34 0 0
#> 170.1 19.54 1 43 0 1
#> 61.1 10.12 1 36 0 1
#> 57.1 14.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 192.1 16.44 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 175.1 21.91 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 37.2 12.52 1 57 1 0
#> 92.1 22.92 1 47 0 1
#> 18 15.21 1 49 1 0
#> 4.2 17.64 1 NA 0 1
#> 10.1 10.53 1 34 0 0
#> 150 20.33 1 48 0 0
#> 136.1 21.83 1 43 0 1
#> 1 24.00 0 23 1 0
#> 163 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 142 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 185 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 147.1 24.00 0 76 1 0
#> 146 24.00 0 63 1 0
#> 83 24.00 0 6 0 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 116 24.00 0 58 0 1
#> 119 24.00 0 17 0 0
#> 27.1 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 35.1 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 147.2 24.00 0 76 1 0
#> 34 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 147.3 24.00 0 76 1 0
#> 144 24.00 0 28 0 1
#> 83.1 24.00 0 6 0 0
#> 186 24.00 0 45 1 0
#> 163.1 24.00 0 66 0 0
#> 35.2 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 119.1 24.00 0 17 0 0
#> 98 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 87.1 24.00 0 27 0 0
#> 95.1 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 1.2 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 173 24.00 0 19 0 1
#> 173.1 24.00 0 19 0 1
#> 162.1 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 137.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 196 24.00 0 19 0 0
#> 22.1 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 196.1 24.00 0 19 0 0
#> 193 24.00 0 45 0 1
#> 31.1 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 54.1 24.00 0 53 1 0
#> 1.3 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 165 24.00 0 47 0 0
#> 198.1 24.00 0 66 0 1
#> 172 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 165.2 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 165.3 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 38 24.00 0 31 1 0
#> 163.2 24.00 0 66 0 0
#> 95.2 24.00 0 68 0 1
#> 196.2 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 87.2 24.00 0 27 0 0
#> 94 24.00 0 51 0 1
#> 118 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 62 24.00 0 71 0 0
#> 132.1 24.00 0 55 0 0
#> 186.1 24.00 0 45 1 0
#> 83.2 24.00 0 6 0 0
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.308 NA NA NA
#> 2 age, Cure model 0.00295 NA NA NA
#> 3 grade_ii, Cure model 0.133 NA NA NA
#> 4 grade_iii, Cure model 0.987 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00332 NA NA NA
#> 2 grade_ii, Survival model 0.229 NA NA NA
#> 3 grade_iii, Survival model 0.178 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.307595 0.002947 0.133493 0.986930
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.307595217 0.002947016 0.133493417 0.986930096
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003318716 0.228517960 0.177714904
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.78427717 0.69743675 0.76865364 0.50227031 0.41790681 0.76865364
#> [7] 0.64910261 0.73731031 0.59896017 0.08445328 0.63238511 0.97139868
#> [13] 0.68138105 0.52053134 0.24908181 0.72147465 0.37793703 0.30472804
#> [19] 0.73731031 0.10287708 0.49302909 0.14834705 0.59896017 0.89068963
#> [25] 0.27177972 0.64910261 0.81522239 0.78427717 0.56446231 0.42773495
#> [31] 0.54694447 0.29372741 0.85323935 0.98570630 0.45583058 0.17490540
#> [37] 0.11980157 0.42773495 0.92032552 0.69743675 0.35762408 0.14834705
#> [43] 0.95691165 0.83060178 0.40797707 0.22562715 0.24908181 0.79976058
#> [49] 0.87581748 0.33648508 0.59896017 0.94231503 0.87581748 0.93498739
#> [55] 0.97139868 0.20086769 0.64076297 0.34709002 0.79976058 0.75300145
#> [61] 0.52053134 0.86829020 0.94962932 0.27177972 0.85323935 0.64910261
#> [67] 0.22562715 0.99286505 0.45583058 0.30472804 0.58171074 0.39790683
#> [73] 0.54694447 0.96416573 0.75300145 0.68138105 0.48374884 0.56446231
#> [79] 0.62399188 0.71344432 0.42773495 0.06362068 0.83060178 0.81522239
#> [85] 0.02634878 0.47439754 0.91292418 0.51143086 0.59034933 0.02634878
#> [91] 0.89813142 0.35762408 0.92032552 0.72147465 0.37793703 0.52053134
#> [97] 0.17490540 0.83060178 0.11980157 0.67327291 0.89813142 0.32582213
#> [103] 0.20086769 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 123 180 155 106 41 155.1 29 13 26 164 6 77 157
#> 13.00 14.82 13.08 16.67 18.02 13.08 15.45 14.34 15.77 23.60 15.64 7.27 15.10
#> 85 99 57 58 128 13.1 129 23 63 26.1 159 90 29.1
#> 16.44 21.19 14.46 19.34 20.35 14.34 23.41 16.92 22.77 15.77 10.55 20.94 15.45
#> 177 123.1 79 40 5 190 42 25 134 175 92 40.1 61
#> 12.53 13.00 16.23 18.00 16.43 20.81 12.43 6.32 17.81 21.91 22.92 18.00 10.12
#> 180.1 170 63.1 16 37 51 153 99.1 14 43 166 26.2 101
#> 14.82 19.54 22.77 8.71 12.52 18.23 21.33 21.19 12.89 12.10 19.98 15.77 9.97
#> 43.1 145 77.1 136 39 105 14.1 81 192 49 183 90.1 42.1
#> 12.10 10.07 7.27 21.83 15.59 19.75 12.89 14.06 16.44 12.19 9.24 20.94 12.43
#> 29.2 153.1 91 134.1 128.1 188 88 5.1 70 81.1 157.1 111 79.1
#> 15.45 21.33 5.33 17.81 20.35 16.16 18.37 16.43 7.38 14.06 15.10 17.45 16.23
#> 125 133 40.2 168 37.1 177.1 24 184 52 171 100 24.1 10
#> 15.65 14.65 18.00 23.72 12.52 12.53 23.89 17.77 10.42 16.57 16.07 23.89 10.53
#> 170.1 61.1 57.1 55 192.1 175.1 37.2 92.1 18 10.1 150 136.1 1
#> 19.54 10.12 14.46 19.34 16.44 21.91 12.52 22.92 15.21 10.53 20.33 21.83 24.00
#> 163 80 95 22 35 147 142 141 185 9 1.1 147.1 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 156 27 54 116 119 27.1 31 35.1 148 147.2 34 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.3 144 83.1 186 163.1 35.2 198 119.1 98 74 87.1 95.1 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.2 120 162 137 173 173.1 162.1 84 137.1 48 135 196 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 196.1 193 31.1 161 54.1 1.3 47 132 165 198.1 172 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.2 67 165.3 28 38 163.2 95.2 196.2 131 104 87.2 94 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 62 132.1 186.1 83.2 65 121 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[30]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0006489141 0.0810550367 -0.2126993182
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.43449069 0.02293295 0.34902328
#> grade_iii, Cure model
#> 0.93497182
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 150 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 167 15.55 1 56 1 0
#> 69 23.23 1 25 0 1
#> 106 16.67 1 49 1 0
#> 37 12.52 1 57 1 0
#> 14 12.89 1 21 0 0
#> 113 22.86 1 34 0 0
#> 117 17.46 1 26 0 1
#> 140 12.68 1 59 1 0
#> 167.1 15.55 1 56 1 0
#> 99 21.19 1 38 0 1
#> 130 16.47 1 53 0 1
#> 55 19.34 1 69 0 1
#> 155 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 136 21.83 1 43 0 1
#> 192.1 16.44 1 31 1 0
#> 195 11.76 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 150.1 20.33 1 48 0 0
#> 30 17.43 1 78 0 0
#> 79 16.23 1 54 1 0
#> 43 12.10 1 61 0 1
#> 14.1 12.89 1 21 0 0
#> 129 23.41 1 53 1 0
#> 187 9.92 1 39 1 0
#> 164 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 136.2 21.83 1 43 0 1
#> 129.1 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 194 22.40 1 38 0 1
#> 159 10.55 1 50 0 1
#> 70 7.38 1 30 1 0
#> 91 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 52 10.42 1 52 0 1
#> 129.2 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 63 22.77 1 31 1 0
#> 76.1 19.22 1 54 0 1
#> 18 15.21 1 49 1 0
#> 134 17.81 1 47 1 0
#> 127 3.53 1 62 0 1
#> 86 23.81 1 58 0 1
#> 50 10.02 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 85 16.44 1 36 0 0
#> 106.1 16.67 1 49 1 0
#> 23 16.92 1 61 0 0
#> 41 18.02 1 40 1 0
#> 167.2 15.55 1 56 1 0
#> 149 8.37 1 33 1 0
#> 157 15.10 1 47 0 0
#> 91.1 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 114.1 13.68 1 NA 0 0
#> 164.1 23.60 1 76 0 1
#> 189 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 63.1 22.77 1 31 1 0
#> 29 15.45 1 68 1 0
#> 56 12.21 1 60 0 0
#> 123 13.00 1 44 1 0
#> 79.1 16.23 1 54 1 0
#> 77.1 7.27 1 67 0 1
#> 93.1 10.33 1 52 0 1
#> 107 11.18 1 54 1 0
#> 181 16.46 1 45 0 1
#> 92 22.92 1 47 0 1
#> 4.2 17.64 1 NA 0 1
#> 127.1 3.53 1 62 0 1
#> 51 18.23 1 83 0 1
#> 199 19.81 1 NA 0 1
#> 97 19.14 1 65 0 1
#> 150.2 20.33 1 48 0 0
#> 92.1 22.92 1 47 0 1
#> 76.2 19.22 1 54 0 1
#> 79.2 16.23 1 54 1 0
#> 6 15.64 1 39 0 0
#> 92.2 22.92 1 47 0 1
#> 55.1 19.34 1 69 0 1
#> 133 14.65 1 57 0 0
#> 61 10.12 1 36 0 1
#> 52.1 10.42 1 52 0 1
#> 13 14.34 1 54 0 1
#> 111.1 17.45 1 47 0 1
#> 199.1 19.81 1 NA 0 1
#> 136.3 21.83 1 43 0 1
#> 192.2 16.44 1 31 1 0
#> 15 22.68 1 48 0 0
#> 55.2 19.34 1 69 0 1
#> 6.1 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 99.1 21.19 1 38 0 1
#> 92.3 22.92 1 47 0 1
#> 93.2 10.33 1 52 0 1
#> 29.1 15.45 1 68 1 0
#> 106.2 16.67 1 49 1 0
#> 189.1 10.51 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 45 17.42 1 54 0 1
#> 105 19.75 1 60 0 0
#> 188 16.16 1 46 0 1
#> 172 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 144 24.00 0 28 0 1
#> 35 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 151 24.00 0 42 0 0
#> 152 24.00 0 36 0 1
#> 131.1 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 17.1 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 98 24.00 0 34 1 0
#> 28 24.00 0 67 1 0
#> 22 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 186 24.00 0 45 1 0
#> 28.1 24.00 0 67 1 0
#> 17.2 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 48 24.00 0 31 1 0
#> 185.1 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 84.1 24.00 0 39 0 1
#> 151.1 24.00 0 42 0 0
#> 34 24.00 0 36 0 0
#> 47 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 193.1 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 71 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 147 24.00 0 76 1 0
#> 34.1 24.00 0 36 0 0
#> 119.1 24.00 0 17 0 0
#> 191 24.00 0 60 0 1
#> 31 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 47.1 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 162 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 137.1 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 3.1 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 162.1 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 143 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 147.2 24.00 0 76 1 0
#> 53.2 24.00 0 32 0 1
#> 98.1 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 141 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 185.2 24.00 0 44 1 0
#> 98.2 24.00 0 34 1 0
#> 165 24.00 0 47 0 0
#> 27 24.00 0 63 1 0
#> 12.1 24.00 0 63 0 0
#> 131.2 24.00 0 66 0 0
#> 34.2 24.00 0 36 0 0
#> 120.1 24.00 0 68 0 1
#> 137.2 24.00 0 45 1 0
#> 104.1 24.00 0 50 1 0
#> 47.2 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 143.1 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 2 24.00 0 9 0 0
#> 54 24.00 0 53 1 0
#> 143.2 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 54.1 24.00 0 53 1 0
#> 82.1 24.00 0 34 0 0
#> 53.3 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.43 NA NA NA
#> 2 age, Cure model 0.0229 NA NA NA
#> 3 grade_ii, Cure model 0.349 NA NA NA
#> 4 grade_iii, Cure model 0.935 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000649 NA NA NA
#> 2 grade_ii, Survival model 0.0811 NA NA NA
#> 3 grade_iii, Survival model -0.213 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.43449 0.02293 0.34902 0.93497
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 243.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.43449069 0.02293295 0.34902328 0.93497182
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0006489141 0.0810550367 -0.2126993182
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.209475024 0.484711333 0.600420759 0.050854025 0.431899028 0.771224772
#> [7] 0.717682104 0.091346758 0.357994629 0.739019371 0.600420759 0.190370475
#> [13] 0.463196879 0.257237794 0.696183795 0.589656611 0.154795335 0.484711333
#> [19] 0.154795335 0.209475024 0.399775835 0.526281358 0.792689595 0.717682104
#> [25] 0.029358828 0.889952807 0.012386503 0.145524217 0.154795335 0.029358828
#> [31] 0.760488448 0.136273216 0.814218290 0.922885031 0.955793476 0.247371591
#> [37] 0.825010253 0.029358828 0.286452481 0.933858886 0.100593403 0.286452481
#> [43] 0.653308864 0.347582371 0.977840902 0.003428593 0.127153215 0.484711333
#> [49] 0.431899028 0.421163830 0.337153938 0.600420759 0.911902883 0.664011398
#> [55] 0.955793476 0.846575463 0.012386503 0.378760749 0.100593403 0.632061705
#> [61] 0.781954370 0.706937353 0.526281358 0.933858886 0.846575463 0.803457336
#> [67] 0.473927870 0.059668242 0.977840902 0.326707229 0.316338123 0.209475024
#> [73] 0.059668242 0.286452481 0.526281358 0.568405836 0.059668242 0.257237794
#> [79] 0.674719119 0.878985270 0.825010253 0.685433018 0.378760749 0.154795335
#> [85] 0.484711333 0.118052681 0.257237794 0.568405836 0.900912603 0.749759321
#> [91] 0.190370475 0.059668242 0.846575463 0.632061705 0.431899028 0.357994629
#> [97] 0.410439256 0.237588865 0.557689391 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 150 192 167 69 106 37 14 113 117 140 167.1 99 130
#> 20.33 16.44 15.55 23.23 16.67 12.52 12.89 22.86 17.46 12.68 15.55 21.19 16.47
#> 55 155 39 136 192.1 136.1 150.1 30 79 43 14.1 129 187
#> 19.34 13.08 15.59 21.83 16.44 21.83 20.33 17.43 16.23 12.10 12.89 23.41 9.92
#> 164 66 136.2 129.1 177 194 159 70 91 170 52 129.2 76
#> 23.60 22.13 21.83 23.41 12.53 22.40 10.55 7.38 5.33 19.54 10.42 23.41 19.22
#> 77 63 76.1 18 134 127 86 169 85 106.1 23 41 167.2
#> 7.27 22.77 19.22 15.21 17.81 3.53 23.81 22.41 16.44 16.67 16.92 18.02 15.55
#> 149 157 91.1 93 164.1 111 63.1 29 56 123 79.1 77.1 93.1
#> 8.37 15.10 5.33 10.33 23.60 17.45 22.77 15.45 12.21 13.00 16.23 7.27 10.33
#> 107 181 92 127.1 51 97 150.2 92.1 76.2 79.2 6 92.2 55.1
#> 11.18 16.46 22.92 3.53 18.23 19.14 20.33 22.92 19.22 16.23 15.64 22.92 19.34
#> 133 61 52.1 13 111.1 136.3 192.2 15 55.2 6.1 16 154 99.1
#> 14.65 10.12 10.42 14.34 17.45 21.83 16.44 22.68 19.34 15.64 8.71 12.63 21.19
#> 92.3 93.2 29.1 106.2 117.1 45 105 188 172 193 144 35 17
#> 22.92 10.33 15.45 16.67 17.46 17.42 19.75 16.16 24.00 24.00 24.00 24.00 24.00
#> 173 137 131 94 151 152 131.1 176 118 185 119 17.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 28 22 12 186 28.1 17.2 120 148 82 48 185.1 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 151.1 34 47 182 193.1 3 71 21 147 34.1 119.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 104 116 47.1 53 162 1 137.1 11 3.1 53.1 162.1 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 163 147.2 53.2 98.1 174 141 112 185.2 98.2 165 27 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.2 34.2 120.1 137.2 104.1 47.2 9 143.1 173.1 2 54 143.2 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 82.1 53.3
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[31]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02314144 0.76455227 0.36859930
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.03516461 -0.00685400 0.05516369
#> grade_iii, Cure model
#> 1.85700255
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 180 14.82 1 37 0 0
#> 4 17.64 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 90 20.94 1 50 0 1
#> 171 16.57 1 41 0 1
#> 76.1 19.22 1 54 0 1
#> 175 21.91 1 43 0 0
#> 123 13.00 1 44 1 0
#> 6 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 100 16.07 1 60 0 0
#> 15 22.68 1 48 0 0
#> 150 20.33 1 48 0 0
#> 145 10.07 1 65 1 0
#> 164 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 43 12.10 1 61 0 1
#> 187 9.92 1 39 1 0
#> 108 18.29 1 39 0 1
#> 113 22.86 1 34 0 0
#> 192 16.44 1 31 1 0
#> 59.1 10.16 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 61 10.12 1 36 0 1
#> 139.1 21.49 1 63 1 0
#> 108.1 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 81 14.06 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 187.1 9.92 1 39 1 0
#> 105 19.75 1 60 0 0
#> 42 12.43 1 49 0 1
#> 105.1 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 157 15.10 1 47 0 0
#> 61.1 10.12 1 36 0 1
#> 70 7.38 1 30 1 0
#> 157.1 15.10 1 47 0 0
#> 26 15.77 1 49 0 1
#> 52 10.42 1 52 0 1
#> 10 10.53 1 34 0 0
#> 49 12.19 1 48 1 0
#> 78 23.88 1 43 0 0
#> 40 18.00 1 28 1 0
#> 99 21.19 1 38 0 1
#> 68 20.62 1 44 0 0
#> 6.1 15.64 1 39 0 0
#> 81.1 14.06 1 34 0 0
#> 91 5.33 1 61 0 1
#> 187.2 9.92 1 39 1 0
#> 155 13.08 1 26 0 0
#> 14 12.89 1 21 0 0
#> 127 3.53 1 62 0 1
#> 150.1 20.33 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 105.2 19.75 1 60 0 0
#> 77.1 7.27 1 67 0 1
#> 90.2 20.94 1 50 0 1
#> 60 13.15 1 38 1 0
#> 79 16.23 1 54 1 0
#> 26.1 15.77 1 49 0 1
#> 32 20.90 1 37 1 0
#> 194 22.40 1 38 0 1
#> 188 16.16 1 46 0 1
#> 39 15.59 1 37 0 1
#> 140 12.68 1 59 1 0
#> 179 18.63 1 42 0 0
#> 50 10.02 1 NA 1 0
#> 42.1 12.43 1 49 0 1
#> 42.2 12.43 1 49 0 1
#> 197.1 21.60 1 69 1 0
#> 108.2 18.29 1 39 0 1
#> 93 10.33 1 52 0 1
#> 154 12.63 1 20 1 0
#> 15.1 22.68 1 48 0 0
#> 167 15.55 1 56 1 0
#> 189.1 10.51 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 189.2 10.51 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 25.1 6.32 1 34 1 0
#> 86 23.81 1 58 0 1
#> 32.1 20.90 1 37 1 0
#> 133 14.65 1 57 0 0
#> 93.1 10.33 1 52 0 1
#> 14.1 12.89 1 21 0 0
#> 6.2 15.64 1 39 0 0
#> 187.3 9.92 1 39 1 0
#> 117.1 17.46 1 26 0 1
#> 106 16.67 1 49 1 0
#> 96.1 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 123.1 13.00 1 44 1 0
#> 113.1 22.86 1 34 0 0
#> 155.1 13.08 1 26 0 0
#> 66 22.13 1 53 0 0
#> 26.2 15.77 1 49 0 1
#> 149.1 8.37 1 33 1 0
#> 105.3 19.75 1 60 0 0
#> 4.1 17.64 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 96.2 14.54 1 33 0 1
#> 101 9.97 1 10 0 1
#> 51 18.23 1 83 0 1
#> 56 12.21 1 60 0 0
#> 190 20.81 1 42 1 0
#> 164.1 23.60 1 76 0 1
#> 2 24.00 0 9 0 0
#> 200 24.00 0 64 0 0
#> 34 24.00 0 36 0 0
#> 47 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 82 24.00 0 34 0 0
#> 62 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 121 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 143.1 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 137 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 67 24.00 0 25 0 0
#> 11 24.00 0 42 0 1
#> 2.1 24.00 0 9 0 0
#> 34.2 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 80 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 178.1 24.00 0 52 1 0
#> 163.1 24.00 0 66 0 0
#> 44.1 24.00 0 56 0 0
#> 186 24.00 0 45 1 0
#> 82.1 24.00 0 34 0 0
#> 27 24.00 0 63 1 0
#> 186.1 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 131 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 109 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 160 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 178.2 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 82.2 24.00 0 34 0 0
#> 146.1 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 186.2 24.00 0 45 1 0
#> 200.1 24.00 0 64 0 0
#> 102.1 24.00 0 49 0 0
#> 142 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 102.2 24.00 0 49 0 0
#> 27.1 24.00 0 63 1 0
#> 156.2 24.00 0 50 1 0
#> 126.1 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 131.1 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 178.3 24.00 0 52 1 0
#> 174.2 24.00 0 49 1 0
#> 103.1 24.00 0 56 1 0
#> 35.1 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 141 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 83.1 24.00 0 6 0 0
#> 3 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 115.1 24.00 0 NA 1 0
#> 121.1 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 11.1 24.00 0 42 0 1
#> 109.1 24.00 0 48 0 0
#> 131.2 24.00 0 66 0 0
#> 146.2 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0352 NA NA NA
#> 2 age, Cure model -0.00685 NA NA NA
#> 3 grade_ii, Cure model 0.0552 NA NA NA
#> 4 grade_iii, Cure model 1.86 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0231 NA NA NA
#> 2 grade_ii, Survival model 0.765 NA NA NA
#> 3 grade_iii, Survival model 0.369 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.035165 -0.006854 0.055164 1.857003
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 235.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.03516461 -0.00685400 0.05516369 1.85700255
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02314144 0.76455227 0.36859930
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 8.842593e-02 9.065742e-03 3.381093e-01 3.623420e-01 2.827094e-02
#> [6] 1.785460e-01 8.842593e-02 7.094129e-03 4.786828e-01 2.614706e-01
#> [11] 1.864365e-02 2.134950e-01 1.986094e-03 5.629205e-02 7.479887e-01
#> [16] 1.576724e-04 1.617744e-01 6.362783e-01 7.813709e-01 1.086154e-01
#> [21] 7.854961e-04 1.871755e-01 1.337122e-02 7.153041e-01 1.864365e-02
#> [26] 1.086154e-01 8.966796e-01 4.119877e-01 2.827094e-02 7.813709e-01
#> [31] 6.594435e-02 5.626835e-01 6.594435e-02 1.460208e-01 3.150676e-01
#> [36] 7.153041e-01 8.799028e-01 3.150676e-01 2.321720e-01 6.673292e-01
#> [41] 6.517030e-01 6.210920e-01 2.766612e-06 1.381027e-01 2.479255e-02
#> [46] 5.178362e-02 2.614706e-01 4.119877e-01 9.649403e-01 7.813709e-01
#> [51] 4.516163e-01 5.060970e-01 9.823676e-01 5.629205e-02 9.307961e-01
#> [56] 6.594435e-02 8.966796e-01 2.827094e-02 4.382422e-01 1.957859e-01
#> [61] 2.321720e-01 3.948419e-02 4.041966e-03 2.045443e-01 2.928618e-01
#> [66] 5.340951e-01 1.015385e-01 5.626835e-01 5.626835e-01 1.337122e-02
#> [71] 1.086154e-01 6.831653e-01 5.484549e-01 1.986094e-03 3.038811e-01
#> [76] 9.065742e-03 2.134950e-01 9.307961e-01 4.137057e-05 3.948419e-02
#> [81] 3.500721e-01 6.831653e-01 5.060970e-01 2.614706e-01 7.813709e-01
#> [86] 1.460208e-01 1.700963e-01 3.623420e-01 8.466234e-01 4.786828e-01
#> [91] 7.854961e-04 4.516163e-01 5.417217e-03 2.321720e-01 8.466234e-01
#> [96] 6.594435e-02 3.990993e-01 3.623420e-01 7.647065e-01 1.301283e-01
#> [101] 6.060136e-01 4.751278e-02 1.576724e-04 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 76 136 180 96 90 171 76.1 175 123 6 139 100 15
#> 19.22 21.83 14.82 14.54 20.94 16.57 19.22 21.91 13.00 15.64 21.49 16.07 22.68
#> 150 145 164 45 43 187 108 113 192 197 61 139.1 108.1
#> 20.33 10.07 23.60 17.42 12.10 9.92 18.29 22.86 16.44 21.60 10.12 21.49 18.29
#> 77 81 90.1 187.1 105 42 105.1 117 157 61.1 70 157.1 26
#> 7.27 14.06 20.94 9.92 19.75 12.43 19.75 17.46 15.10 10.12 7.38 15.10 15.77
#> 52 10 49 78 40 99 68 6.1 81.1 91 187.2 155 14
#> 10.42 10.53 12.19 23.88 18.00 21.19 20.62 15.64 14.06 5.33 9.92 13.08 12.89
#> 127 150.1 25 105.2 77.1 90.2 60 79 26.1 32 194 188 39
#> 3.53 20.33 6.32 19.75 7.27 20.94 13.15 16.23 15.77 20.90 22.40 16.16 15.59
#> 140 179 42.1 42.2 197.1 108.2 93 154 15.1 167 136.1 100.1 25.1
#> 12.68 18.63 12.43 12.43 21.60 18.29 10.33 12.63 22.68 15.55 21.83 16.07 6.32
#> 86 32.1 133 93.1 14.1 6.2 187.3 117.1 106 96.1 149 123.1 113.1
#> 23.81 20.90 14.65 10.33 12.89 15.64 9.92 17.46 16.67 14.54 8.37 13.00 22.86
#> 155.1 66 26.2 149.1 105.3 13 96.2 101 51 56 190 164.1 2
#> 13.08 22.13 15.77 8.37 19.75 14.34 14.54 9.97 18.23 12.21 20.81 23.60 24.00
#> 200 34 47 143 9 34.1 156 172 75 82 62 165 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 121 53 143.1 126 174 174.1 137 44 67 11 2.1 34.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 33 151 80 102 178.1 163.1 44.1 186 82.1 27 186.1 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 1 109 83 35 146 198 160 156.1 120 178.2 87 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 84 186.2 200.1 102.1 142 122 22 102.2 27.1 156.2 126.1 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 48 1.1 178.3 174.2 103.1 35.1 87.1 141 54 83.1 3 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 20 11.1 109.1 131.2 146.2 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[32]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.000489906 0.154367869 0.277114109
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.106687589 -0.008100385 0.368152238
#> grade_iii, Cure model
#> 1.054300733
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 166 19.98 1 48 0 0
#> 128 20.35 1 35 0 1
#> 63 22.77 1 31 1 0
#> 81 14.06 1 34 0 0
#> 60 13.15 1 38 1 0
#> 177 12.53 1 75 0 0
#> 117 17.46 1 26 0 1
#> 96 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 139 21.49 1 63 1 0
#> 125 15.65 1 67 1 0
#> 40 18.00 1 28 1 0
#> 55 19.34 1 69 0 1
#> 158 20.14 1 74 1 0
#> 188 16.16 1 46 0 1
#> 107 11.18 1 54 1 0
#> 149 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 57 14.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 90 20.94 1 50 0 1
#> 192 16.44 1 31 1 0
#> 4.1 17.64 1 NA 0 1
#> 57.1 14.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 195 11.76 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 6 15.64 1 39 0 0
#> 43 12.10 1 61 0 1
#> 37 12.52 1 57 1 0
#> 56 12.21 1 60 0 0
#> 154 12.63 1 20 1 0
#> 179 18.63 1 42 0 0
#> 57.2 14.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 123 13.00 1 44 1 0
#> 4.2 17.64 1 NA 0 1
#> 195.1 11.76 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 128.1 20.35 1 35 0 1
#> 139.1 21.49 1 63 1 0
#> 43.1 12.10 1 61 0 1
#> 61 10.12 1 36 0 1
#> 61.1 10.12 1 36 0 1
#> 128.2 20.35 1 35 0 1
#> 127 3.53 1 62 0 1
#> 26.1 15.77 1 49 0 1
#> 153 21.33 1 55 1 0
#> 183 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 14 12.89 1 21 0 0
#> 170 19.54 1 43 0 1
#> 159 10.55 1 50 0 1
#> 37.1 12.52 1 57 1 0
#> 166.1 19.98 1 48 0 0
#> 194 22.40 1 38 0 1
#> 179.1 18.63 1 42 0 0
#> 159.1 10.55 1 50 0 1
#> 37.2 12.52 1 57 1 0
#> 4.3 17.64 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 79 16.23 1 54 1 0
#> 192.1 16.44 1 31 1 0
#> 180 14.82 1 37 0 0
#> 100.1 16.07 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 97 19.14 1 65 0 1
#> 63.1 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 125.1 15.65 1 67 1 0
#> 129 23.41 1 53 1 0
#> 154.1 12.63 1 20 1 0
#> 49 12.19 1 48 1 0
#> 56.1 12.21 1 60 0 0
#> 81.1 14.06 1 34 0 0
#> 57.3 14.46 1 45 0 1
#> 43.2 12.10 1 61 0 1
#> 108 18.29 1 39 0 1
#> 55.1 19.34 1 69 0 1
#> 108.1 18.29 1 39 0 1
#> 111 17.45 1 47 0 1
#> 101 9.97 1 10 0 1
#> 51 18.23 1 83 0 1
#> 149.1 8.37 1 33 1 0
#> 81.2 14.06 1 34 0 0
#> 40.1 18.00 1 28 1 0
#> 150.1 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 108.2 18.29 1 39 0 1
#> 175.1 21.91 1 43 0 0
#> 179.2 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 171 16.57 1 41 0 1
#> 78 23.88 1 43 0 0
#> 159.2 10.55 1 50 0 1
#> 16 8.71 1 71 0 1
#> 154.2 12.63 1 20 1 0
#> 14.1 12.89 1 21 0 0
#> 129.1 23.41 1 53 1 0
#> 136 21.83 1 43 0 1
#> 91 5.33 1 61 0 1
#> 36 21.19 1 48 0 1
#> 157 15.10 1 47 0 0
#> 199.1 19.81 1 NA 0 1
#> 105.1 19.75 1 60 0 0
#> 24 23.89 1 38 0 0
#> 181 16.46 1 45 0 1
#> 32 20.90 1 37 1 0
#> 55.2 19.34 1 69 0 1
#> 32.1 20.90 1 37 1 0
#> 43.3 12.10 1 61 0 1
#> 38 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 11 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 28 24.00 0 67 1 0
#> 82 24.00 0 34 0 0
#> 151 24.00 0 42 0 0
#> 67.1 24.00 0 25 0 0
#> 21 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 95.1 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 62 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 47 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 22.1 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 174 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 120.1 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 72 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 135.1 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 7 24.00 0 37 1 0
#> 200 24.00 0 64 0 0
#> 109 24.00 0 48 0 0
#> 46 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 135.2 24.00 0 58 1 0
#> 135.3 24.00 0 58 1 0
#> 193.2 24.00 0 45 0 1
#> 34.1 24.00 0 36 0 0
#> 186 24.00 0 45 1 0
#> 115.1 24.00 0 NA 1 0
#> 142 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 132 24.00 0 55 0 0
#> 62.1 24.00 0 71 0 0
#> 20.1 24.00 0 46 1 0
#> 156 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 17.1 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 193.3 24.00 0 45 0 1
#> 19 24.00 0 57 0 1
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 47.1 24.00 0 38 0 1
#> 142.1 24.00 0 53 0 0
#> 22.2 24.00 0 52 1 0
#> 186.1 24.00 0 45 1 0
#> 132.1 24.00 0 55 0 0
#> 83 24.00 0 6 0 0
#> 165.1 24.00 0 47 0 0
#> 19.1 24.00 0 57 0 1
#> 165.2 24.00 0 47 0 0
#> 104 24.00 0 50 1 0
#> 102.1 24.00 0 49 0 0
#> 163 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 178 24.00 0 52 1 0
#> 11.1 24.00 0 42 0 1
#> 46.1 24.00 0 71 0 0
#> 163.1 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 142.2 24.00 0 53 0 0
#> 22.3 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.107 NA NA NA
#> 2 age, Cure model -0.00810 NA NA NA
#> 3 grade_ii, Cure model 0.368 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000490 NA NA NA
#> 2 grade_ii, Survival model 0.154 NA NA NA
#> 3 grade_iii, Survival model 0.277 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.1067 -0.0081 0.3682 1.0543
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 251.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.106687589 -0.008100385 0.368152238 1.054300733
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.000489906 0.154367869 0.277114109
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.31633868 0.25556106 0.10475578 0.71986803 0.74520492 0.80423706
#> [7] 0.50823310 0.67755476 0.65130027 0.17756913 0.62508307 0.48051119
#> [13] 0.36691127 0.30603976 0.58088692 0.89522581 0.96805691 0.52665457
#> [19] 0.68626563 0.09106564 0.22309091 0.55402099 0.68626563 0.47114195
#> [25] 0.58982258 0.64252275 0.86267374 0.81268472 0.83761143 0.77914958
#> [31] 0.40540500 0.68626563 0.60754268 0.75372966 0.33657085 0.25556106
#> [37] 0.17756913 0.86267374 0.92771532 0.92771532 0.25556106 0.99202695
#> [43] 0.60754268 0.20023140 0.95194230 0.28564692 0.76223590 0.35676717
#> [49] 0.90346216 0.81268472 0.31633868 0.12927487 0.40540500 0.90346216
#> [55] 0.81268472 0.57190298 0.55402099 0.66880556 0.58982258 0.39566570
#> [61] 0.10475578 0.14175122 0.62508307 0.06452359 0.77914958 0.85430286
#> [67] 0.83761143 0.71986803 0.68626563 0.86267374 0.43388581 0.36691127
#> [73] 0.43388581 0.51747253 0.94385851 0.46173717 0.96805691 0.71986803
#> [79] 0.48051119 0.28564692 0.04812145 0.43388581 0.14175122 0.40540500
#> [85] 0.49893685 0.53583039 0.02947526 0.90346216 0.96001198 0.77914958
#> [91] 0.76223590 0.06452359 0.16553034 0.98403076 0.21176922 0.66005426
#> [97] 0.33657085 0.01104519 0.54495216 0.23421404 0.36691127 0.23421404
#> [103] 0.86267374 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 166 128 63 81 60 177 117 96 167 139 125 40 55
#> 19.98 20.35 22.77 14.06 13.15 12.53 17.46 14.54 15.55 21.49 15.65 18.00 19.34
#> 158 188 107 149 30 57 69 90 192 57.1 41 100 6
#> 20.14 16.16 11.18 8.37 17.43 14.46 23.23 20.94 16.44 14.46 18.02 16.07 15.64
#> 43 37 56 154 179 57.2 26 123 105 128.1 139.1 43.1 61
#> 12.10 12.52 12.21 12.63 18.63 14.46 15.77 13.00 19.75 20.35 21.49 12.10 10.12
#> 61.1 128.2 127 26.1 153 183 150 14 170 159 37.1 166.1 194
#> 10.12 20.35 3.53 15.77 21.33 9.24 20.33 12.89 19.54 10.55 12.52 19.98 22.40
#> 179.1 159.1 37.2 79 192.1 180 100.1 97 63.1 175 125.1 129 154.1
#> 18.63 10.55 12.52 16.23 16.44 14.82 16.07 19.14 22.77 21.91 15.65 23.41 12.63
#> 49 56.1 81.1 57.3 43.2 108 55.1 108.1 111 101 51 149.1 81.2
#> 12.19 12.21 14.06 14.46 12.10 18.29 19.34 18.29 17.45 9.97 18.23 8.37 14.06
#> 40.1 150.1 164 108.2 175.1 179.2 184 171 78 159.2 16 154.2 14.1
#> 18.00 20.33 23.60 18.29 21.91 18.63 17.77 16.57 23.88 10.55 8.71 12.63 12.89
#> 129.1 136 91 36 157 105.1 24 181 32 55.2 32.1 43.3 38
#> 23.41 21.83 5.33 21.19 15.10 19.75 23.89 16.46 20.90 19.34 20.90 12.10 24.00
#> 22 135 11 185 95 67 162 103 28 82 151 67.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 144 95.1 64 62 47 12 22.1 34 174 193 33 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 102 72 31 198 135.1 1 7 200 109 46 137 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 135.2 135.3 193.2 34.1 186 142 20 132 62.1 20.1 156 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 146 17 141 1.1 17.1 165 161 193.3 19 143 87 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 22.2 186.1 132.1 83 165.1 19.1 165.2 104 102.1 163 119 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 46.1 163.1 160 131 142.2 22.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[33]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004169529 0.123515411 -0.063852256
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.179248416 0.002675151 -0.016607412
#> grade_iii, Cure model
#> 0.692356296
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 85 16.44 1 36 0 0
#> 110 17.56 1 65 0 1
#> 133 14.65 1 57 0 0
#> 110.1 17.56 1 65 0 1
#> 26 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 189 10.51 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 52 10.42 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 179 18.63 1 42 0 0
#> 180 14.82 1 37 0 0
#> 179.1 18.63 1 42 0 0
#> 49 12.19 1 48 1 0
#> 37 12.52 1 57 1 0
#> 69 23.23 1 25 0 1
#> 114 13.68 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 76 19.22 1 54 0 1
#> 39 15.59 1 37 0 1
#> 56 12.21 1 60 0 0
#> 110.2 17.56 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 85.1 16.44 1 36 0 0
#> 40 18.00 1 28 1 0
#> 42 12.43 1 49 0 1
#> 88 18.37 1 47 0 0
#> 194 22.40 1 38 0 1
#> 129 23.41 1 53 1 0
#> 199 19.81 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 199.1 19.81 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 110.3 17.56 1 65 0 1
#> 58 19.34 1 39 0 0
#> 175 21.91 1 43 0 0
#> 189.1 10.51 1 NA 1 0
#> 189.2 10.51 1 NA 1 0
#> 181.1 16.46 1 45 0 1
#> 5 16.43 1 51 0 1
#> 69.1 23.23 1 25 0 1
#> 190.1 20.81 1 42 1 0
#> 153 21.33 1 55 1 0
#> 88.1 18.37 1 47 0 0
#> 154 12.63 1 20 1 0
#> 26.1 15.77 1 49 0 1
#> 49.1 12.19 1 48 1 0
#> 170 19.54 1 43 0 1
#> 39.1 15.59 1 37 0 1
#> 5.1 16.43 1 51 0 1
#> 199.2 19.81 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 68.1 20.62 1 44 0 0
#> 194.1 22.40 1 38 0 1
#> 149 8.37 1 33 1 0
#> 85.2 16.44 1 36 0 0
#> 136.1 21.83 1 43 0 1
#> 145 10.07 1 65 1 0
#> 85.3 16.44 1 36 0 0
#> 93 10.33 1 52 0 1
#> 6.1 15.64 1 39 0 0
#> 93.1 10.33 1 52 0 1
#> 39.2 15.59 1 37 0 1
#> 100 16.07 1 60 0 0
#> 79 16.23 1 54 1 0
#> 16 8.71 1 71 0 1
#> 45 17.42 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 49.2 12.19 1 48 1 0
#> 59.1 10.16 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 39.3 15.59 1 37 0 1
#> 79.1 16.23 1 54 1 0
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 189.3 10.51 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 113 22.86 1 34 0 0
#> 184 17.77 1 38 0 0
#> 91 5.33 1 61 0 1
#> 153.2 21.33 1 55 1 0
#> 139.1 21.49 1 63 1 0
#> 167 15.55 1 56 1 0
#> 18 15.21 1 49 1 0
#> 128 20.35 1 35 0 1
#> 81 14.06 1 34 0 0
#> 10 10.53 1 34 0 0
#> 159 10.55 1 50 0 1
#> 164 23.60 1 76 0 1
#> 145.1 10.07 1 65 1 0
#> 179.2 18.63 1 42 0 0
#> 166 19.98 1 48 0 0
#> 117 17.46 1 26 0 1
#> 86 23.81 1 58 0 1
#> 37.1 12.52 1 57 1 0
#> 123 13.00 1 44 1 0
#> 107 11.18 1 54 1 0
#> 183 9.24 1 67 1 0
#> 45.1 17.42 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 123.1 13.00 1 44 1 0
#> 40.1 18.00 1 28 1 0
#> 57 14.46 1 45 0 1
#> 175.2 21.91 1 43 0 0
#> 190.2 20.81 1 42 1 0
#> 128.1 20.35 1 35 0 1
#> 58.1 19.34 1 39 0 0
#> 115 24.00 0 NA 1 0
#> 138 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 80 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 19 24.00 0 57 0 1
#> 19.1 24.00 0 57 0 1
#> 147 24.00 0 76 1 0
#> 2 24.00 0 9 0 0
#> 11.1 24.00 0 42 0 1
#> 147.1 24.00 0 76 1 0
#> 11.2 24.00 0 42 0 1
#> 135 24.00 0 58 1 0
#> 193 24.00 0 45 0 1
#> 82 24.00 0 34 0 0
#> 46 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 138.1 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 141 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 35.1 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 152 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 12 24.00 0 63 0 0
#> 122 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 20.1 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 132 24.00 0 55 0 0
#> 151 24.00 0 42 0 0
#> 98 24.00 0 34 1 0
#> 83.1 24.00 0 6 0 0
#> 147.2 24.00 0 76 1 0
#> 162 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 7.2 24.00 0 37 1 0
#> 161 24.00 0 45 0 0
#> 147.3 24.00 0 76 1 0
#> 95.1 24.00 0 68 0 1
#> 122.1 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 82.1 24.00 0 34 0 0
#> 7.3 24.00 0 37 1 0
#> 72 24.00 0 40 0 1
#> 62 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 109.1 24.00 0 48 0 0
#> 82.2 24.00 0 34 0 0
#> 3 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 48 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 196.1 24.00 0 19 0 0
#> 165 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 47 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 65 24.00 0 57 1 0
#> 138.2 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 185.1 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 54.1 24.00 0 53 1 0
#> 191.1 24.00 0 60 0 1
#> 103 24.00 0 56 1 0
#> 28.1 24.00 0 67 1 0
#> 142 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 98.1 24.00 0 34 1 0
#> 21.1 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 144 24.00 0 28 0 1
#> 109.2 24.00 0 48 0 0
#> 72.2 24.00 0 40 0 1
#> 182 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.179 NA NA NA
#> 2 age, Cure model 0.00268 NA NA NA
#> 3 grade_ii, Cure model -0.0166 NA NA NA
#> 4 grade_iii, Cure model 0.692 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00417 NA NA NA
#> 2 grade_ii, Survival model 0.124 NA NA NA
#> 3 grade_iii, Survival model -0.0639 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.179248 0.002675 -0.016607 0.692356
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.179248416 0.002675151 -0.016607412 0.692356296
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004169529 0.123515411 -0.063852256
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.58605348 0.50257537 0.76479714 0.50257537 0.66754560 0.68544678
#> [7] 0.28280831 0.91808628 0.91808628 0.41540927 0.75598542 0.41540927
#> [13] 0.86816914 0.83424867 0.08702922 0.20364057 0.15451727 0.40533758
#> [19] 0.70326583 0.85969201 0.50257537 0.44450342 0.58605348 0.47376657
#> [25] 0.85119106 0.45438963 0.12825995 0.05969583 0.31354670 0.56750550
#> [31] 0.50257537 0.38535869 0.16796209 0.56750550 0.62219859 0.08702922
#> [37] 0.28280831 0.25086651 0.45438963 0.81703387 0.66754560 0.86816914
#> [43] 0.37514165 0.70326583 0.62219859 0.80838903 0.31354670 0.12825995
#> [49] 0.98374947 0.58605348 0.20364057 0.95108736 0.58605348 0.93461089
#> [55] 0.68544678 0.93461089 0.70326583 0.65849736 0.64045523 0.97559712
#> [61] 0.54887735 0.86816914 0.25086651 0.70326583 0.64045523 0.22782838
#> [67] 0.35457510 0.16796209 0.82565774 0.11408724 0.49293077 0.99188172
#> [73] 0.25086651 0.22782838 0.73828700 0.74715654 0.33411456 0.78235314
#> [79] 0.90976158 0.90142527 0.03990410 0.95108736 0.41540927 0.36489047
#> [85] 0.53942628 0.01727949 0.83424867 0.79110963 0.89307695 0.96742692
#> [91] 0.54887735 0.05969583 0.79110963 0.47376657 0.77358170 0.16796209
#> [97] 0.28280831 0.33411456 0.38535869 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 85 110 133 110.1 26 6 190 52 52.1 179 180 179.1 49
#> 16.44 17.56 14.65 17.56 15.77 15.64 20.81 10.42 10.42 18.63 14.82 18.63 12.19
#> 37 69 136 66 76 39 56 110.2 8 85.1 40 42 88
#> 12.52 23.23 21.83 22.13 19.22 15.59 12.21 17.56 18.43 16.44 18.00 12.43 18.37
#> 194 129 68 181 110.3 58 175 181.1 5 69.1 190.1 153 88.1
#> 22.40 23.41 20.62 16.46 17.56 19.34 21.91 16.46 16.43 23.23 20.81 21.33 18.37
#> 154 26.1 49.1 170 39.1 5.1 140 68.1 194.1 149 85.2 136.1 145
#> 12.63 15.77 12.19 19.54 15.59 16.43 12.68 20.62 22.40 8.37 16.44 21.83 10.07
#> 85.3 93 6.1 93.1 39.2 100 79 16 45 49.2 153.1 39.3 79.1
#> 16.44 10.33 15.64 10.33 15.59 16.07 16.23 8.71 17.42 12.19 21.33 15.59 16.23
#> 139 150 175.1 177 113 184 91 153.2 139.1 167 18 128 81
#> 21.49 20.33 21.91 12.53 22.86 17.77 5.33 21.33 21.49 15.55 15.21 20.35 14.06
#> 10 159 164 145.1 179.2 166 117 86 37.1 123 107 183 45.1
#> 10.53 10.55 23.60 10.07 18.63 19.98 17.46 23.81 12.52 13.00 11.18 9.24 17.42
#> 129.1 123.1 40.1 57 175.2 190.2 128.1 58.1 138 83 35 20 80
#> 23.41 13.00 18.00 14.46 21.91 20.81 20.35 19.34 24.00 24.00 24.00 24.00 24.00
#> 11 19 19.1 147 2 11.1 147.1 11.2 135 193 82 46 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 138.1 7 141 54 35.1 95 112 152 119 21 143 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 122 185 7.1 20.1 198 132 151 98 83.1 147.2 162 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.2 161 147.3 95.1 122.1 109 118 82.1 7.3 72 62 53 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.2 3 198.1 48 84 196.1 165 191 47 65 138.2 48.1 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 54.1 191.1 103 28.1 142 142.1 98.1 21.1 160 103.1 144 109.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.2 182
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[34]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002426989 0.471419743 0.393049345
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.201819175 0.002036576 -0.027795681
#> grade_iii, Cure model
#> 0.979134583
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 110 17.56 1 65 0 1
#> 77 7.27 1 67 0 1
#> 171 16.57 1 41 0 1
#> 45 17.42 1 54 0 1
#> 25 6.32 1 34 1 0
#> 70 7.38 1 30 1 0
#> 149 8.37 1 33 1 0
#> 108 18.29 1 39 0 1
#> 50 10.02 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 49 12.19 1 48 1 0
#> 25.1 6.32 1 34 1 0
#> 184 17.77 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 24 23.89 1 38 0 0
#> 184.1 17.77 1 38 0 0
#> 76 19.22 1 54 0 1
#> 25.2 6.32 1 34 1 0
#> 61 10.12 1 36 0 1
#> 194 22.40 1 38 0 1
#> 92 22.92 1 47 0 1
#> 13 14.34 1 54 0 1
#> 153 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 125 15.65 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 56 12.21 1 60 0 0
#> 125.1 15.65 1 67 1 0
#> 52 10.42 1 52 0 1
#> 14 12.89 1 21 0 0
#> 58 19.34 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 190 20.81 1 42 1 0
#> 55 19.34 1 69 0 1
#> 129 23.41 1 53 1 0
#> 5 16.43 1 51 0 1
#> 106 16.67 1 49 1 0
#> 63 22.77 1 31 1 0
#> 15 22.68 1 48 0 0
#> 130 16.47 1 53 0 1
#> 130.1 16.47 1 53 0 1
#> 181 16.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 169 22.41 1 46 0 0
#> 107 11.18 1 54 1 0
#> 169.1 22.41 1 46 0 0
#> 56.1 12.21 1 60 0 0
#> 171.1 16.57 1 41 0 1
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 58.1 19.34 1 39 0 0
#> 127 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 113 22.86 1 34 0 0
#> 187 9.92 1 39 1 0
#> 194.1 22.40 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 55.1 19.34 1 69 0 1
#> 61.1 10.12 1 36 0 1
#> 61.2 10.12 1 36 0 1
#> 187.1 9.92 1 39 1 0
#> 42 12.43 1 49 0 1
#> 89.1 11.44 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 51 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 76.1 19.22 1 54 0 1
#> 23 16.92 1 61 0 0
#> 117 17.46 1 26 0 1
#> 145 10.07 1 65 1 0
#> 13.1 14.34 1 54 0 1
#> 197 21.60 1 69 1 0
#> 108.1 18.29 1 39 0 1
#> 55.2 19.34 1 69 0 1
#> 4.1 17.64 1 NA 0 1
#> 14.1 12.89 1 21 0 0
#> 10.1 10.53 1 34 0 0
#> 105 19.75 1 60 0 0
#> 76.2 19.22 1 54 0 1
#> 184.2 17.77 1 38 0 0
#> 25.3 6.32 1 34 1 0
#> 133 14.65 1 57 0 0
#> 76.3 19.22 1 54 0 1
#> 29 15.45 1 68 1 0
#> 61.3 10.12 1 36 0 1
#> 6 15.64 1 39 0 0
#> 49.2 12.19 1 48 1 0
#> 63.1 22.77 1 31 1 0
#> 157.1 15.10 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 43 12.10 1 61 0 1
#> 192 16.44 1 31 1 0
#> 133.1 14.65 1 57 0 0
#> 150 20.33 1 48 0 0
#> 179 18.63 1 42 0 0
#> 150.1 20.33 1 48 0 0
#> 78 23.88 1 43 0 0
#> 110.1 17.56 1 65 0 1
#> 10.2 10.53 1 34 0 0
#> 55.3 19.34 1 69 0 1
#> 110.2 17.56 1 65 0 1
#> 197.1 21.60 1 69 1 0
#> 81 14.06 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 184.3 17.77 1 38 0 0
#> 88 18.37 1 47 0 0
#> 167 15.55 1 56 1 0
#> 145.1 10.07 1 65 1 0
#> 59 10.16 1 NA 1 0
#> 13.2 14.34 1 54 0 1
#> 184.4 17.77 1 38 0 0
#> 186 24.00 0 45 1 0
#> 137 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 118 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 119 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 65 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 146 24.00 0 63 1 0
#> 119.2 24.00 0 17 0 0
#> 178 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 132 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 28.1 24.00 0 67 1 0
#> 102 24.00 0 49 0 0
#> 132.1 24.00 0 55 0 0
#> 7 24.00 0 37 1 0
#> 137.1 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 71 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 27 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 1 24.00 0 23 1 0
#> 174 24.00 0 49 1 0
#> 156 24.00 0 50 1 0
#> 95.1 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 20 24.00 0 46 1 0
#> 33.1 24.00 0 53 0 0
#> 122.1 24.00 0 66 0 0
#> 35.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 193 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 121 24.00 0 57 1 0
#> 121.1 24.00 0 57 1 0
#> 28.2 24.00 0 67 1 0
#> 53 24.00 0 32 0 1
#> 94 24.00 0 51 0 1
#> 138 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 9.1 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 20.1 24.00 0 46 1 0
#> 35.2 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 191.1 24.00 0 60 0 1
#> 22 24.00 0 52 1 0
#> 75.1 24.00 0 21 1 0
#> 109.2 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 17 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 104 24.00 0 50 1 0
#> 38 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 64 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 103 24.00 0 56 1 0
#> 71.1 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 9.2 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 64.1 24.00 0 43 0 0
#> 31 24.00 0 36 0 1
#> 82.1 24.00 0 34 0 0
#> 142 24.00 0 53 0 0
#> 38.1 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.202 NA NA NA
#> 2 age, Cure model 0.00204 NA NA NA
#> 3 grade_ii, Cure model -0.0278 NA NA NA
#> 4 grade_iii, Cure model 0.979 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00243 NA NA NA
#> 2 grade_ii, Survival model 0.471 NA NA NA
#> 3 grade_iii, Survival model 0.393 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.201819 0.002037 -0.027796 0.979135
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 252.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.201819175 0.002036576 -0.027795681 0.979134583
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002426989 0.471419743 0.393049345
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.46119470 0.94395334 0.52750548 0.49904652 0.96022358 0.93574604
#> [7] 0.92750333 0.38515564 0.62759546 0.78466487 0.96022358 0.41424781
#> [13] 0.78466487 0.00823933 0.41424781 0.32713783 0.96022358 0.86124663
#> [19] 0.14765577 0.05841437 0.70669904 0.20486024 0.82730357 0.60075830
#> [25] 0.76731203 0.60075830 0.85271632 0.74125172 0.26976363 0.94395334
#> [31] 0.21603340 0.26976363 0.04282680 0.58260600 0.51805990 0.08741498
#> [37] 0.11080045 0.54600360 0.54600360 0.56431404 0.22695426 0.12334083
#> [43] 0.81876542 0.12334083 0.76731203 0.52750548 0.67171608 0.26976363
#> [49] 0.99198127 0.17065269 0.07279584 0.91102133 0.14765577 0.26976363
#> [55] 0.86124663 0.86124663 0.91102133 0.75861282 0.59167272 0.40450460
#> [61] 0.66295192 0.32713783 0.50854098 0.48949766 0.89440177 0.70669904
#> [67] 0.18265038 0.38515564 0.26976363 0.74125172 0.82730357 0.25888011
#> [73] 0.32713783 0.41424781 0.96022358 0.68917887 0.32713783 0.65413852
#> [79] 0.86124663 0.61859837 0.78466487 0.08741498 0.67171608 0.62759546
#> [85] 0.81019101 0.57349547 0.68917887 0.23768887 0.36523316 0.23768887
#> [91] 0.02466860 0.46119470 0.82730357 0.26976363 0.46119470 0.18265038
#> [97] 0.73252996 0.41424781 0.37518014 0.64528235 0.89440177 0.70669904
#> [103] 0.41424781 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 110 77 171 45 25 70 149 108 39 49 25.1 184 49.1
#> 17.56 7.27 16.57 17.42 6.32 7.38 8.37 18.29 15.59 12.19 6.32 17.77 12.19
#> 24 184.1 76 25.2 61 194 92 13 153 10 125 56 125.1
#> 23.89 17.77 19.22 6.32 10.12 22.40 22.92 14.34 21.33 10.53 15.65 12.21 15.65
#> 52 14 58 77.1 190 55 129 5 106 63 15 130 130.1
#> 10.42 12.89 19.34 7.27 20.81 19.34 23.41 16.43 16.67 22.77 22.68 16.47 16.47
#> 181 128 169 107 169.1 56.1 171.1 157 58.1 127 175 113 187
#> 16.46 20.35 22.41 11.18 22.41 12.21 16.57 15.10 19.34 3.53 21.91 22.86 9.92
#> 194.1 55.1 61.1 61.2 187.1 42 100 51 18 76.1 23 117 145
#> 22.40 19.34 10.12 10.12 9.92 12.43 16.07 18.23 15.21 19.22 16.92 17.46 10.07
#> 13.1 197 108.1 55.2 14.1 10.1 105 76.2 184.2 25.3 133 76.3 29
#> 14.34 21.60 18.29 19.34 12.89 10.53 19.75 19.22 17.77 6.32 14.65 19.22 15.45
#> 61.3 6 49.2 63.1 157.1 39.1 43 192 133.1 150 179 150.1 78
#> 10.12 15.64 12.19 22.77 15.10 15.59 12.10 16.44 14.65 20.33 18.63 20.33 23.88
#> 110.1 10.2 55.3 110.2 197.1 81 184.3 88 167 145.1 13.2 184.4 186
#> 17.56 10.53 19.34 17.56 21.60 14.06 17.77 18.37 15.55 10.07 14.34 17.77 24.00
#> 137 9 28 118 173 120 33 84 119 11 65 35 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 146 119.2 178 165 132 75 176 46 95 28.1 102 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 137.1 131 87 71 102.1 109 109.1 44 27 62 54 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 156 95.1 120.1 20 33.1 122.1 35.1 182 193 191 121 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.2 53 94 138 82 9.1 143 20.1 35.2 2 191.1 22 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.2 83 17 116 104 38 34 64 126 34.1 103 71.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 12 64.1 31 82.1 142 38.1 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[35]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007856781 0.880172462 0.337179961
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.61136123 0.01540097 0.18161579
#> grade_iii, Cure model
#> 0.14673065
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 97 19.14 1 65 0 1
#> 164 23.60 1 76 0 1
#> 105 19.75 1 60 0 0
#> 133 14.65 1 57 0 0
#> 25 6.32 1 34 1 0
#> 167 15.55 1 56 1 0
#> 32 20.90 1 37 1 0
#> 149 8.37 1 33 1 0
#> 181 16.46 1 45 0 1
#> 81 14.06 1 34 0 0
#> 159 10.55 1 50 0 1
#> 187 9.92 1 39 1 0
#> 52 10.42 1 52 0 1
#> 149.1 8.37 1 33 1 0
#> 166 19.98 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 113 22.86 1 34 0 0
#> 69 23.23 1 25 0 1
#> 5 16.43 1 51 0 1
#> 194 22.40 1 38 0 1
#> 189 10.51 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 175 21.91 1 43 0 0
#> 81.1 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 149.2 8.37 1 33 1 0
#> 41 18.02 1 40 1 0
#> 70 7.38 1 30 1 0
#> 188 16.16 1 46 0 1
#> 49 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 158 20.14 1 74 1 0
#> 169 22.41 1 46 0 0
#> 139.1 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 57 14.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 194.1 22.40 1 38 0 1
#> 145 10.07 1 65 1 0
#> 124 9.73 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 99 21.19 1 38 0 1
#> 6 15.64 1 39 0 0
#> 139.2 21.49 1 63 1 0
#> 57.2 14.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 51 18.23 1 83 0 1
#> 164.1 23.60 1 76 0 1
#> 177 12.53 1 75 0 0
#> 77 7.27 1 67 0 1
#> 63 22.77 1 31 1 0
#> 170 19.54 1 43 0 1
#> 136 21.83 1 43 0 1
#> 149.3 8.37 1 33 1 0
#> 108 18.29 1 39 0 1
#> 155 13.08 1 26 0 0
#> 140 12.68 1 59 1 0
#> 183 9.24 1 67 1 0
#> 100 16.07 1 60 0 0
#> 157 15.10 1 47 0 0
#> 168 23.72 1 70 0 0
#> 149.4 8.37 1 33 1 0
#> 23 16.92 1 61 0 0
#> 13 14.34 1 54 0 1
#> 16.1 8.71 1 71 0 1
#> 130.1 16.47 1 53 0 1
#> 166.1 19.98 1 48 0 0
#> 78 23.88 1 43 0 0
#> 166.2 19.98 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 81.2 14.06 1 34 0 0
#> 69.1 23.23 1 25 0 1
#> 25.1 6.32 1 34 1 0
#> 125 15.65 1 67 1 0
#> 154 12.63 1 20 1 0
#> 179 18.63 1 42 0 0
#> 105.1 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 40 18.00 1 28 1 0
#> 26 15.77 1 49 0 1
#> 76 19.22 1 54 0 1
#> 5.1 16.43 1 51 0 1
#> 56 12.21 1 60 0 0
#> 81.3 14.06 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 117.1 17.46 1 26 0 1
#> 134 17.81 1 47 1 0
#> 78.1 23.88 1 43 0 0
#> 32.1 20.90 1 37 1 0
#> 108.1 18.29 1 39 0 1
#> 184 17.77 1 38 0 0
#> 26.1 15.77 1 49 0 1
#> 189.1 10.51 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 164.2 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 145.1 10.07 1 65 1 0
#> 195 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 8.1 18.43 1 32 0 0
#> 56.1 12.21 1 60 0 0
#> 145.2 10.07 1 65 1 0
#> 85 16.44 1 36 0 0
#> 24 23.89 1 38 0 0
#> 195.1 11.76 1 NA 1 0
#> 164.3 23.60 1 76 0 1
#> 24.1 23.89 1 38 0 0
#> 21 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 132 24.00 0 55 0 0
#> 152 24.00 0 36 0 1
#> 21.1 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 64 24.00 0 43 0 0
#> 144 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 144.1 24.00 0 28 0 1
#> 73 24.00 0 NA 0 1
#> 87 24.00 0 27 0 0
#> 185 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 82 24.00 0 34 0 0
#> 31 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 21.2 24.00 0 47 0 0
#> 173 24.00 0 19 0 1
#> 131.1 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#> 176 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 47 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 31.1 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 172 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 160 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 116 24.00 0 58 0 1
#> 84.1 24.00 0 39 0 1
#> 144.2 24.00 0 28 0 1
#> 185.1 24.00 0 44 1 0
#> 84.2 24.00 0 39 0 1
#> 19.2 24.00 0 57 0 1
#> 162.2 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 142 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 84.3 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 146 24.00 0 63 1 0
#> 151.1 24.00 0 42 0 0
#> 148 24.00 0 61 1 0
#> 178 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 173.1 24.00 0 19 0 1
#> 174 24.00 0 49 1 0
#> 196 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 147 24.00 0 76 1 0
#> 163.1 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 173.2 24.00 0 19 0 1
#> 148.1 24.00 0 61 1 0
#> 122 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 20 24.00 0 46 1 0
#> 71.1 24.00 0 51 0 0
#> 20.1 24.00 0 46 1 0
#> 176.1 24.00 0 43 0 1
#> 72.1 24.00 0 40 0 1
#> 62 24.00 0 71 0 0
#> 156 24.00 0 50 1 0
#> 44.1 24.00 0 56 0 0
#> 53 24.00 0 32 0 1
#> 95 24.00 0 68 0 1
#> 98.2 24.00 0 34 1 0
#> 7 24.00 0 37 1 0
#> 11.1 24.00 0 42 0 1
#> 65 24.00 0 57 1 0
#> 73.2 24.00 0 NA 0 1
#> 84.4 24.00 0 39 0 1
#> 48.2 24.00 0 31 1 0
#> 11.2 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.611 NA NA NA
#> 2 age, Cure model 0.0154 NA NA NA
#> 3 grade_ii, Cure model 0.182 NA NA NA
#> 4 grade_iii, Cure model 0.147 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00786 NA NA NA
#> 2 grade_ii, Survival model 0.880 NA NA NA
#> 3 grade_iii, Survival model 0.337 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.6114 0.0154 0.1816 0.1467
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 257.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.61136123 0.01540097 0.18161579 0.14673065
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007856781 0.880172462 0.337179961
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.334249295 0.046268478 0.295750543 0.624621163 0.982741087 0.605192633
#> [7] 0.231675127 0.912604669 0.508083214 0.682909173 0.809006238 0.866146110
#> [13] 0.818683097 0.912604669 0.268242383 0.183018653 0.106538000 0.085040339
#> [19] 0.527446186 0.139876927 0.211970888 0.894027486 0.634414238 0.160866168
#> [25] 0.682909173 0.460224309 0.912604669 0.403121040 0.956450728 0.546718549
#> [31] 0.799335643 0.770300717 0.488954338 0.259048172 0.128891718 0.183018653
#> [37] 0.249738961 0.644195084 0.644195084 0.139876927 0.828367843 0.956450728
#> [43] 0.221831585 0.595415492 0.183018653 0.644195084 0.856645694 0.393118871
#> [49] 0.046268478 0.760647950 0.973942096 0.118183692 0.314838370 0.171942051
#> [55] 0.912604669 0.373502143 0.721760357 0.731700839 0.884728600 0.556445327
#> [61] 0.614883204 0.034733711 0.912604669 0.479323513 0.673115653 0.894027486
#> [67] 0.488954338 0.268242383 0.017470573 0.268242383 0.866146110 0.682909173
#> [73] 0.085040339 0.982741087 0.585680541 0.741572014 0.344012100 0.295750543
#> [79] 0.441514989 0.412937862 0.566236440 0.324531719 0.527446186 0.779959134
#> [85] 0.682909173 0.741572014 0.441514989 0.422541210 0.017470573 0.231675127
#> [91] 0.373502143 0.432001210 0.566236440 0.046268478 0.469765813 0.828367843
#> [97] 0.353853418 0.353853418 0.779959134 0.828367843 0.517742398 0.004538537
#> [103] 0.046268478 0.004538537 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 97 164 105 133 25 167 32 149 181 81 159 187 52
#> 19.14 23.60 19.75 14.65 6.32 15.55 20.90 8.37 16.46 14.06 10.55 9.92 10.42
#> 149.1 166 139 113 69 5 194 153 16 96 175 81.1 30
#> 8.37 19.98 21.49 22.86 23.23 16.43 22.40 21.33 8.71 14.54 21.91 14.06 17.43
#> 149.2 41 70 188 49 42 130 158 169 139.1 150 57 57.1
#> 8.37 18.02 7.38 16.16 12.19 12.43 16.47 20.14 22.41 21.49 20.33 14.46 14.46
#> 194.1 145 70.1 99 6 139.2 57.2 101 51 164.1 177 77 63
#> 22.40 10.07 7.38 21.19 15.64 21.49 14.46 9.97 18.23 23.60 12.53 7.27 22.77
#> 170 136 149.3 108 155 140 183 100 157 168 149.4 23 13
#> 19.54 21.83 8.37 18.29 13.08 12.68 9.24 16.07 15.10 23.72 8.37 16.92 14.34
#> 16.1 130.1 166.1 78 166.2 187.1 81.2 69.1 25.1 125 154 179 105.1
#> 8.71 16.47 19.98 23.88 19.98 9.92 14.06 23.23 6.32 15.65 12.63 18.63 19.75
#> 117 40 26 76 5.1 56 81.3 154.1 117.1 134 78.1 32.1 108.1
#> 17.46 18.00 15.77 19.22 16.43 12.21 14.06 12.63 17.46 17.81 23.88 20.90 18.29
#> 184 26.1 164.2 45 145.1 8 8.1 56.1 145.2 85 24 164.3 24.1
#> 17.77 15.77 23.60 17.42 10.07 18.43 18.43 12.21 10.07 16.44 23.89 23.60 23.89
#> 21 151 132 152 21.1 162 11 64 144 131 144.1 87 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 82 31 9 19 21.2 173 131.1 19.1 176 143 44 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 31.1 163 104 162.1 84 172 71 34 160 116 84.1 144.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 84.2 19.2 162.2 98 142 48 3 84.3 74 116.1 146 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 178 72 173.1 174 196 200 147 163.1 48.1 160.1 47.1 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 122 98.1 20 71.1 20.1 176.1 72.1 62 156 44.1 53 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 7 11.1 65 84.4 48.2 11.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[36]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01971785 0.58303349 0.50631180
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.485130700 0.006950752 0.039329533
#> grade_iii, Cure model
#> 1.147359788
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 89 11.44 1 NA 0 0
#> 150 20.33 1 48 0 0
#> 111 17.45 1 47 0 1
#> 91 5.33 1 61 0 1
#> 180 14.82 1 37 0 0
#> 10 10.53 1 34 0 0
#> 32 20.90 1 37 1 0
#> 86 23.81 1 58 0 1
#> 195 11.76 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 23 16.92 1 61 0 0
#> 40 18.00 1 28 1 0
#> 86.1 23.81 1 58 0 1
#> 60 13.15 1 38 1 0
#> 89.1 11.44 1 NA 0 0
#> 105 19.75 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 39 15.59 1 37 0 1
#> 13 14.34 1 54 0 1
#> 18 15.21 1 49 1 0
#> 124 9.73 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 91.1 5.33 1 61 0 1
#> 70 7.38 1 30 1 0
#> 4 17.64 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 166 19.98 1 48 0 0
#> 77 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 42 12.43 1 49 0 1
#> 14.1 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 15 22.68 1 48 0 0
#> 134 17.81 1 47 1 0
#> 192 16.44 1 31 1 0
#> 105.1 19.75 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 158 20.14 1 74 1 0
#> 16 8.71 1 71 0 1
#> 49 12.19 1 48 1 0
#> 197.1 21.60 1 69 1 0
#> 124.1 9.73 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 85 16.44 1 36 0 0
#> 18.1 15.21 1 49 1 0
#> 164 23.60 1 76 0 1
#> 114 13.68 1 NA 0 0
#> 91.2 5.33 1 61 0 1
#> 177 12.53 1 75 0 0
#> 79 16.23 1 54 1 0
#> 88 18.37 1 47 0 0
#> 168 23.72 1 70 0 0
#> 179 18.63 1 42 0 0
#> 111.2 17.45 1 47 0 1
#> 129 23.41 1 53 1 0
#> 60.1 13.15 1 38 1 0
#> 45 17.42 1 54 0 1
#> 155 13.08 1 26 0 0
#> 140 12.68 1 59 1 0
#> 76 19.22 1 54 0 1
#> 70.1 7.38 1 30 1 0
#> 49.1 12.19 1 48 1 0
#> 25 6.32 1 34 1 0
#> 127 3.53 1 62 0 1
#> 167 15.55 1 56 1 0
#> 149 8.37 1 33 1 0
#> 105.2 19.75 1 60 0 0
#> 130 16.47 1 53 0 1
#> 59 10.16 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 86.2 23.81 1 58 0 1
#> 114.1 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 25.1 6.32 1 34 1 0
#> 61 10.12 1 36 0 1
#> 56 12.21 1 60 0 0
#> 192.1 16.44 1 31 1 0
#> 106 16.67 1 49 1 0
#> 57 14.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 177.1 12.53 1 75 0 0
#> 100 16.07 1 60 0 0
#> 8 18.43 1 32 0 0
#> 26 15.77 1 49 0 1
#> 88.1 18.37 1 47 0 0
#> 16.1 8.71 1 71 0 1
#> 130.1 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 55 19.34 1 69 0 1
#> 42.1 12.43 1 49 0 1
#> 157 15.10 1 47 0 0
#> 40.1 18.00 1 28 1 0
#> 149.1 8.37 1 33 1 0
#> 195.1 11.76 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 171 16.57 1 41 0 1
#> 86.3 23.81 1 58 0 1
#> 52 10.42 1 52 0 1
#> 26.1 15.77 1 49 0 1
#> 164.1 23.60 1 76 0 1
#> 127.1 3.53 1 62 0 1
#> 39.1 15.59 1 37 0 1
#> 139 21.49 1 63 1 0
#> 15.1 22.68 1 48 0 0
#> 93.1 10.33 1 52 0 1
#> 139.1 21.49 1 63 1 0
#> 24.1 23.89 1 38 0 0
#> 199.2 19.81 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 20 24.00 0 46 1 0
#> 34 24.00 0 36 0 0
#> 38 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 87 24.00 0 27 0 0
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 156.1 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#> 31 24.00 0 36 0 1
#> 34.1 24.00 0 36 0 0
#> 95 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 38.1 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 33 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 126 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 186 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 38.2 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 142.1 24.00 0 53 0 0
#> 186.1 24.00 0 45 1 0
#> 12.1 24.00 0 63 0 0
#> 198.1 24.00 0 66 0 1
#> 115.1 24.00 0 NA 1 0
#> 2 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 115.2 24.00 0 NA 1 0
#> 35 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 186.2 24.00 0 45 1 0
#> 200.1 24.00 0 64 0 0
#> 9 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 73.1 24.00 0 NA 0 1
#> 62 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 186.3 24.00 0 45 1 0
#> 165.1 24.00 0 47 0 0
#> 19 24.00 0 57 0 1
#> 7.1 24.00 0 37 1 0
#> 137 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 44 24.00 0 56 0 0
#> 31.1 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 3.1 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 62.1 24.00 0 71 0 0
#> 144 24.00 0 28 0 1
#> 98 24.00 0 34 1 0
#> 112.1 24.00 0 61 0 0
#> 38.3 24.00 0 31 1 0
#> 186.4 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 196.1 24.00 0 19 0 0
#> 54 24.00 0 53 1 0
#> 80 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 132 24.00 0 55 0 0
#> 64 24.00 0 43 0 0
#> 44.1 24.00 0 56 0 0
#> 47.1 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 172.1 24.00 0 41 0 0
#> 148.2 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 196.2 24.00 0 19 0 0
#> 162.1 24.00 0 51 0 0
#> 27.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.485 NA NA NA
#> 2 age, Cure model 0.00695 NA NA NA
#> 3 grade_ii, Cure model 0.0393 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0197 NA NA NA
#> 2 grade_ii, Survival model 0.583 NA NA NA
#> 3 grade_iii, Survival model 0.506 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.485131 0.006951 0.039330 1.147360
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 250.9
#> Residual Deviance: 239 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.485130700 0.006950752 0.039329533 1.147359788
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01971785 0.58303349 0.50631180
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0598880464 0.1800810985 0.9157572976 0.4171440032 0.6766290194
#> [6] 0.0547168344 0.0012308119 0.0124743636 0.2172855939 0.1450078772
#> [11] 0.0012308119 0.4810350478 0.0771258543 0.3457339334 0.4550758118
#> [16] 0.3808205847 0.0150434213 0.9157572976 0.8342484294 0.5203353109
#> [21] 0.0710876373 0.8665431444 0.0278216824 0.5888218477 0.5203353109
#> [26] 0.0001484068 0.0178470186 0.1620427393 0.2689460206 0.0771258543
#> [31] 0.1800810985 0.0446993810 0.0653478478 0.7697654275 0.6320950738
#> [36] 0.0278216824 0.6615589952 0.2689460206 0.3808205847 0.0061516276
#> [41] 0.9157572976 0.5607474623 0.3004845086 0.1279123231 0.0045483380
#> [46] 0.1118261734 0.1800810985 0.0100759254 0.4810350478 0.2075130985
#> [51] 0.5070288144 0.5470658154 0.1042131259 0.8342484294 0.6320950738
#> [56] 0.8830165102 0.9657603513 0.3688968522 0.8019644494 0.0771258543
#> [61] 0.2479611720 0.7538905587 0.0012308119 0.0496116903 0.8830165102
#> [66] 0.7381882804 0.6173986612 0.2689460206 0.2273756132 0.4423385415
#> [71] 0.0241334294 0.4679674969 0.5607474623 0.3115416284 0.1197428272
#> [76] 0.3228778507 0.1279123231 0.7697654275 0.2479611720 0.7072376900
#> [81] 0.0968309752 0.5888218477 0.4047648035 0.1450078772 0.8019644494
#> [86] 0.1709364526 0.2376102393 0.0012308119 0.6918648159 0.3228778507
#> [91] 0.0061516276 0.9657603513 0.3457339334 0.0357792996 0.0178470186
#> [96] 0.7072376900 0.0357792996 0.0001484068 0.4297164374 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000
#>
#> $Time
#> 150 111 91 180 10 32 86 92 23 40 86.1 60 105
#> 20.33 17.45 5.33 14.82 10.53 20.90 23.81 22.92 16.92 18.00 23.81 13.15 19.75
#> 39 13 18 113 91.1 70 14 166 77 197 42 14.1 24
#> 15.59 14.34 15.21 22.86 5.33 7.38 12.89 19.98 7.27 21.60 12.43 12.89 23.89
#> 15 134 192 105.1 111.1 153 158 16 49 197.1 43 85 18.1
#> 22.68 17.81 16.44 19.75 17.45 21.33 20.14 8.71 12.19 21.60 12.10 16.44 15.21
#> 164 91.2 177 79 88 168 179 111.2 129 60.1 45 155 140
#> 23.60 5.33 12.53 16.23 18.37 23.72 18.63 17.45 23.41 13.15 17.42 13.08 12.68
#> 76 70.1 49.1 25 127 167 149 105.2 130 183 86.2 90 25.1
#> 19.22 7.38 12.19 6.32 3.53 15.55 8.37 19.75 16.47 9.24 23.81 20.94 6.32
#> 61 56 192.1 106 57 169 81 177.1 100 8 26 88.1 16.1
#> 10.12 12.21 16.44 16.67 14.46 22.41 14.06 12.53 16.07 18.43 15.77 18.37 8.71
#> 130.1 93 55 42.1 157 40.1 149.1 184 171 86.3 52 26.1 164.1
#> 16.47 10.33 19.34 12.43 15.10 18.00 8.37 17.77 16.57 23.81 10.42 15.77 23.60
#> 127.1 39.1 139 15.1 93.1 139.1 24.1 96 20 34 38 142 198
#> 3.53 15.59 21.49 22.68 10.33 21.49 23.89 14.54 24.00 24.00 24.00 24.00 24.00
#> 156 131 116 87 12 112 156.1 148 31 34.1 95 104 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 131.1 200 84 33 135 126 3 196 186 172 38.2 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 12.1 198.1 2 165 160 7 35 28 186.2 200.1 9 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 162 186.3 165.1 19 7.1 137 148.1 44 31.1 21 47 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 147 62.1 144 98 112.1 38.3 186.4 72 196.1 54 80 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 132 64 44.1 47.1 27 172.1 148.2 141 20.1 196.2 162.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[37]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0007823629 0.6057032095 0.3337222256
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.99228544 0.01403321 0.45483905
#> grade_iii, Cure model
#> 1.06940754
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 6 15.64 1 39 0 0
#> 199 19.81 1 NA 0 1
#> 91 5.33 1 61 0 1
#> 128 20.35 1 35 0 1
#> 170 19.54 1 43 0 1
#> 93 10.33 1 52 0 1
#> 170.1 19.54 1 43 0 1
#> 187 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 90 20.94 1 50 0 1
#> 63 22.77 1 31 1 0
#> 99 21.19 1 38 0 1
#> 99.1 21.19 1 38 0 1
#> 93.1 10.33 1 52 0 1
#> 81 14.06 1 34 0 0
#> 105 19.75 1 60 0 0
#> 43 12.10 1 61 0 1
#> 107 11.18 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 181 16.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 199.1 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 41.1 18.02 1 40 1 0
#> 100 16.07 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 59 10.16 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 111 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 88 18.37 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 23.1 16.92 1 61 0 0
#> 45 17.42 1 54 0 1
#> 150.1 20.33 1 48 0 0
#> 81.1 14.06 1 34 0 0
#> 140 12.68 1 59 1 0
#> 114 13.68 1 NA 0 0
#> 164 23.60 1 76 0 1
#> 157 15.10 1 47 0 0
#> 106 16.67 1 49 1 0
#> 42 12.43 1 49 0 1
#> 43.1 12.10 1 61 0 1
#> 192 16.44 1 31 1 0
#> 177 12.53 1 75 0 0
#> 85 16.44 1 36 0 0
#> 58 19.34 1 39 0 0
#> 136 21.83 1 43 0 1
#> 153 21.33 1 55 1 0
#> 139.1 21.49 1 63 1 0
#> 168 23.72 1 70 0 0
#> 125 15.65 1 67 1 0
#> 90.1 20.94 1 50 0 1
#> 91.1 5.33 1 61 0 1
#> 128.1 20.35 1 35 0 1
#> 195.1 11.76 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 99.2 21.19 1 38 0 1
#> 14 12.89 1 21 0 0
#> 16 8.71 1 71 0 1
#> 180 14.82 1 37 0 0
#> 51 18.23 1 83 0 1
#> 15 22.68 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 45.1 17.42 1 54 0 1
#> 57 14.46 1 45 0 1
#> 187.1 9.92 1 39 1 0
#> 60 13.15 1 38 1 0
#> 59.1 10.16 1 NA 1 0
#> 45.2 17.42 1 54 0 1
#> 32 20.90 1 37 1 0
#> 61 10.12 1 36 0 1
#> 181.1 16.46 1 45 0 1
#> 106.1 16.67 1 49 1 0
#> 158 20.14 1 74 1 0
#> 124.1 9.73 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 60.1 13.15 1 38 1 0
#> 18 15.21 1 49 1 0
#> 69 23.23 1 25 0 1
#> 57.1 14.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 149 8.37 1 33 1 0
#> 106.2 16.67 1 49 1 0
#> 110 17.56 1 65 0 1
#> 140.1 12.68 1 59 1 0
#> 96.1 14.54 1 33 0 1
#> 25 6.32 1 34 1 0
#> 192.1 16.44 1 31 1 0
#> 59.2 10.16 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 170.2 19.54 1 43 0 1
#> 5 16.43 1 51 0 1
#> 15.1 22.68 1 48 0 0
#> 145.1 10.07 1 65 1 0
#> 10 10.53 1 34 0 0
#> 61.1 10.12 1 36 0 1
#> 111.1 17.45 1 47 0 1
#> 66 22.13 1 53 0 0
#> 10.1 10.53 1 34 0 0
#> 86 23.81 1 58 0 1
#> 166 19.98 1 48 0 0
#> 90.2 20.94 1 50 0 1
#> 49 12.19 1 48 1 0
#> 90.3 20.94 1 50 0 1
#> 98 24.00 0 34 1 0
#> 98.1 24.00 0 34 1 0
#> 119 24.00 0 17 0 0
#> 62 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 120 24.00 0 68 0 1
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 33 24.00 0 53 0 0
#> 119.1 24.00 0 17 0 0
#> 182 24.00 0 35 0 0
#> 48.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 162 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 103 24.00 0 56 1 0
#> 67 24.00 0 25 0 0
#> 173.1 24.00 0 19 0 1
#> 44.1 24.00 0 56 0 0
#> 186 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 73.1 24.00 0 NA 0 1
#> 62.1 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 196 24.00 0 19 0 0
#> 141 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 173.2 24.00 0 19 0 1
#> 31 24.00 0 36 0 1
#> 103.1 24.00 0 56 1 0
#> 200 24.00 0 64 0 0
#> 12.1 24.00 0 63 0 0
#> 176 24.00 0 43 0 1
#> 73.2 24.00 0 NA 0 1
#> 109 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 152 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 115 24.00 0 NA 1 0
#> 95 24.00 0 68 0 1
#> 11 24.00 0 42 0 1
#> 65 24.00 0 57 1 0
#> 119.2 24.00 0 17 0 0
#> 186.1 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 7 24.00 0 37 1 0
#> 44.2 24.00 0 56 0 0
#> 38 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 186.2 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 162.2 24.00 0 51 0 0
#> 44.3 24.00 0 56 0 0
#> 3 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 147 24.00 0 76 1 0
#> 17 24.00 0 38 0 1
#> 182.1 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 193.1 24.00 0 45 0 1
#> 152.1 24.00 0 36 0 1
#> 116.1 24.00 0 58 0 1
#> 11.1 24.00 0 42 0 1
#> 131 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 82 24.00 0 34 0 0
#> 135 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 83.1 24.00 0 6 0 0
#> 198.1 24.00 0 66 0 1
#> 200.1 24.00 0 64 0 0
#> 118 24.00 0 44 1 0
#> 109.1 24.00 0 48 0 0
#> 31.1 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.992 NA NA NA
#> 2 age, Cure model 0.0140 NA NA NA
#> 3 grade_ii, Cure model 0.455 NA NA NA
#> 4 grade_iii, Cure model 1.07 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000782 NA NA NA
#> 2 grade_ii, Survival model 0.606 NA NA NA
#> 3 grade_iii, Survival model 0.334 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99229 0.01403 0.45484 1.06941
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 252.5
#> Residual Deviance: 241.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99228544 0.01403321 0.45483905 1.06940754
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0007823629 0.6057032095 0.3337222256
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.01859551 0.01859551 0.70690328 0.98524806 0.36063900 0.43233957
#> [7] 0.89390472 0.43233957 0.94018742 0.22611793 0.38113688 0.30850448
#> [13] 0.12403582 0.27526011 0.27526011 0.89390472 0.77375545 0.42210759
#> [19] 0.85465834 0.87040376 0.49148445 0.62071490 0.51053336 0.68984762
#> [25] 0.49148445 0.68124461 0.67264658 0.57580754 0.52971616 0.97032176
#> [31] 0.47158135 0.57580754 0.54843703 0.38113688 0.77375545 0.81464488
#> [37] 0.08958754 0.72381184 0.59422972 0.83868458 0.85465834 0.63832424
#> [43] 0.83064246 0.63832424 0.46160573 0.19831841 0.25159242 0.22611793
#> [49] 0.07069542 0.69841392 0.30850448 0.98524806 0.36063900 0.16798257
#> [55] 0.27526011 0.80648570 0.95526691 0.73223152 0.48156460 0.13915251
#> [61] 0.19831841 0.54843703 0.75726761 0.94018742 0.79025253 0.54843703
#> [67] 0.35002083 0.90945837 0.62071490 0.59422972 0.40167573 0.74065395
#> [73] 0.79025253 0.71539571 0.10731732 0.75726761 0.92491754 0.96281746
#> [79] 0.59422972 0.52015366 0.81464488 0.74065395 0.97780725 0.63832424
#> [85] 0.25159242 0.43233957 0.66401026 0.13915251 0.92491754 0.87825839
#> [91] 0.90945837 0.52971616 0.18312463 0.87825839 0.05209642 0.41188698
#> [97] 0.30850448 0.84670028 0.30850448 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 24 24.1 6 91 128 170 93 170.1 187 139 150 90 63
#> 23.89 23.89 15.64 5.33 20.35 19.54 10.33 19.54 9.92 21.49 20.33 20.94 22.77
#> 99 99.1 93.1 81 105 43 107 41 181 184 26 41.1 100
#> 21.19 21.19 10.33 14.06 19.75 12.10 11.18 18.02 16.46 17.77 15.77 18.02 16.07
#> 188 23 111 77 88 23.1 45 150.1 81.1 140 164 157 106
#> 16.16 16.92 17.45 7.27 18.37 16.92 17.42 20.33 14.06 12.68 23.60 15.10 16.67
#> 42 43.1 192 177 85 58 136 153 139.1 168 125 90.1 91.1
#> 12.43 12.10 16.44 12.53 16.44 19.34 21.83 21.33 21.49 23.72 15.65 20.94 5.33
#> 128.1 169 99.2 14 16 180 51 15 136.1 45.1 57 187.1 60
#> 20.35 22.41 21.19 12.89 8.71 14.82 18.23 22.68 21.83 17.42 14.46 9.92 13.15
#> 45.2 32 61 181.1 106.1 158 96 60.1 18 69 57.1 145 149
#> 17.42 20.90 10.12 16.46 16.67 20.14 14.54 13.15 15.21 23.23 14.46 10.07 8.37
#> 106.2 110 140.1 96.1 25 192.1 153.1 170.2 5 15.1 145.1 10 61.1
#> 16.67 17.56 12.68 14.54 6.32 16.44 21.33 19.54 16.43 22.68 10.07 10.53 10.12
#> 111.1 66 10.1 86 166 90.2 49 90.3 98 98.1 119 62 173
#> 17.45 22.13 10.53 23.81 19.98 20.94 12.19 20.94 24.00 24.00 24.00 24.00 24.00
#> 120 44 102 12 48 33 119.1 182 48.1 185 132 162 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 103 67 173.1 44.1 186 198 62.1 34 196 141 71 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 116 173.2 31 103.1 200 12.1 176 109 83 152 156 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 95 11 65 119.2 186.1 84 7 44.2 38 141.1 122 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.2 27 19 162.2 44.3 3 38.1 132.1 147 17 182.1 1 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 116.1 11.1 131 161 82 135 142 83.1 198.1 200.1 118 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[38]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007064583 0.191977719 0.095455983
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.80659569 0.01912557 0.01275597
#> grade_iii, Cure model
#> 0.39482706
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 63 22.77 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 18 15.21 1 49 1 0
#> 14 12.89 1 21 0 0
#> 15 22.68 1 48 0 0
#> 81 14.06 1 34 0 0
#> 90 20.94 1 50 0 1
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 187 9.92 1 39 1 0
#> 177 12.53 1 75 0 0
#> 197 21.60 1 69 1 0
#> 108 18.29 1 39 0 1
#> 85 16.44 1 36 0 0
#> 14.1 12.89 1 21 0 0
#> 158 20.14 1 74 1 0
#> 86 23.81 1 58 0 1
#> 63.1 22.77 1 31 1 0
#> 66 22.13 1 53 0 0
#> 197.1 21.60 1 69 1 0
#> 124 9.73 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 25 6.32 1 34 1 0
#> 108.1 18.29 1 39 0 1
#> 23 16.92 1 61 0 0
#> 154 12.63 1 20 1 0
#> 43 12.10 1 61 0 1
#> 55 19.34 1 69 0 1
#> 188 16.16 1 46 0 1
#> 168 23.72 1 70 0 0
#> 57 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 85.1 16.44 1 36 0 0
#> 168.1 23.72 1 70 0 0
#> 10 10.53 1 34 0 0
#> 125 15.65 1 67 1 0
#> 56 12.21 1 60 0 0
#> 100 16.07 1 60 0 0
#> 110 17.56 1 65 0 1
#> 24 23.89 1 38 0 0
#> 85.2 16.44 1 36 0 0
#> 14.2 12.89 1 21 0 0
#> 183 9.24 1 67 1 0
#> 127 3.53 1 62 0 1
#> 60 13.15 1 38 1 0
#> 140.1 12.68 1 59 1 0
#> 37 12.52 1 57 1 0
#> 13 14.34 1 54 0 1
#> 107 11.18 1 54 1 0
#> 55.1 19.34 1 69 0 1
#> 124.1 9.73 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 110.1 17.56 1 65 0 1
#> 129 23.41 1 53 1 0
#> 177.1 12.53 1 75 0 0
#> 4 17.64 1 NA 0 1
#> 41 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 96.1 14.54 1 33 0 1
#> 90.1 20.94 1 50 0 1
#> 139 21.49 1 63 1 0
#> 139.1 21.49 1 63 1 0
#> 175 21.91 1 43 0 0
#> 175.1 21.91 1 43 0 0
#> 61 10.12 1 36 0 1
#> 190.1 20.81 1 42 1 0
#> 194 22.40 1 38 0 1
#> 197.2 21.60 1 69 1 0
#> 18.1 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 111 17.45 1 47 0 1
#> 108.2 18.29 1 39 0 1
#> 133 14.65 1 57 0 0
#> 41.1 18.02 1 40 1 0
#> 197.3 21.60 1 69 1 0
#> 181 16.46 1 45 0 1
#> 5 16.43 1 51 0 1
#> 179 18.63 1 42 0 0
#> 134 17.81 1 47 1 0
#> 60.1 13.15 1 38 1 0
#> 154.1 12.63 1 20 1 0
#> 170 19.54 1 43 0 1
#> 51 18.23 1 83 0 1
#> 40 18.00 1 28 1 0
#> 40.1 18.00 1 28 1 0
#> 23.1 16.92 1 61 0 0
#> 145 10.07 1 65 1 0
#> 57.1 14.46 1 45 0 1
#> 114.1 13.68 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 16 8.71 1 71 0 1
#> 70 7.38 1 30 1 0
#> 111.1 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 77.1 7.27 1 67 0 1
#> 13.1 14.34 1 54 0 1
#> 23.2 16.92 1 61 0 0
#> 189 10.51 1 NA 1 0
#> 197.4 21.60 1 69 1 0
#> 18.2 15.21 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 177.2 12.53 1 75 0 0
#> 69 23.23 1 25 0 1
#> 158.1 20.14 1 74 1 0
#> 194.1 22.40 1 38 0 1
#> 10.1 10.53 1 34 0 0
#> 49 12.19 1 48 1 0
#> 187.1 9.92 1 39 1 0
#> 86.1 23.81 1 58 0 1
#> 182 24.00 0 35 0 0
#> 162 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 65 24.00 0 57 1 0
#> 22 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 82 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 120 24.00 0 68 0 1
#> 48 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 74 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 152 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 75 24.00 0 21 1 0
#> 48.1 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 54 24.00 0 53 1 0
#> 135 24.00 0 58 1 0
#> 22.1 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 172 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 9 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 121 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 48.2 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 38 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 22.2 24.00 0 52 1 0
#> 163 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 174.1 24.00 0 49 1 0
#> 118 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 73.1 24.00 0 NA 0 1
#> 11.1 24.00 0 42 0 1
#> 53.1 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 1.1 24.00 0 23 1 0
#> 178 24.00 0 52 1 0
#> 162.1 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 119 24.00 0 17 0 0
#> 44 24.00 0 56 0 0
#> 19.1 24.00 0 57 0 1
#> 147.2 24.00 0 76 1 0
#> 54.1 24.00 0 53 1 0
#> 160 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 11.2 24.00 0 42 0 1
#> 173 24.00 0 19 0 1
#> 11.3 24.00 0 42 0 1
#> 21 24.00 0 47 0 0
#> 75.1 24.00 0 21 1 0
#> 67 24.00 0 25 0 0
#> 152.1 24.00 0 36 0 1
#> 34.2 24.00 0 36 0 0
#> 191.1 24.00 0 60 0 1
#> 200.1 24.00 0 64 0 0
#> 138 24.00 0 44 1 0
#> 121.1 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 71.1 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 64 24.00 0 43 0 0
#> 137 24.00 0 45 1 0
#> 73.2 24.00 0 NA 0 1
#> 12 24.00 0 63 0 0
#> 141 24.00 0 44 1 0
#> 48.3 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.807 NA NA NA
#> 2 age, Cure model 0.0191 NA NA NA
#> 3 grade_ii, Cure model 0.0128 NA NA NA
#> 4 grade_iii, Cure model 0.395 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00706 NA NA NA
#> 2 grade_ii, Survival model 0.192 NA NA NA
#> 3 grade_iii, Survival model 0.0955 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.80660 0.01913 0.01276 0.39483
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 254.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.80659569 0.01912557 0.01275597 0.39482706
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007064583 0.191977719 0.095455983
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.215884106 0.037200508 0.881805888 0.504664420 0.655246889 0.049213394
#> [7] 0.611334658 0.156851099 0.382586593 0.546742583 0.893534759 0.732469296
#> [13] 0.097280412 0.251291135 0.432386574 0.655246889 0.190009232 0.005533943
#> [19] 0.037200508 0.068924649 0.097280412 0.688082161 0.976077526 0.251291135
#> [25] 0.392481617 0.710293726 0.800477491 0.215884106 0.473121691 0.013595057
#> [31] 0.568099918 0.173350788 0.432386574 0.013595057 0.835191145 0.494087174
#> [37] 0.777514903 0.483565174 0.334516788 0.001496246 0.432386574 0.655246889
#> [43] 0.916887387 0.988017763 0.622332917 0.688082161 0.766103203 0.589618677
#> [49] 0.812017439 0.215884106 0.148576145 0.068924649 0.334516788 0.024295094
#> [55] 0.732469296 0.287708852 0.353576978 0.546742583 0.156851099 0.132673319
#> [61] 0.132673319 0.082782426 0.082782426 0.858377297 0.173350788 0.055891045
#> [67] 0.097280412 0.504664420 0.644191519 0.363261452 0.251291135 0.536012045
#> [73] 0.287708852 0.097280412 0.422192300 0.462725278 0.242120815 0.325014583
#> [79] 0.622332917 0.710293726 0.207090162 0.278281975 0.306358242 0.306358242
#> [85] 0.392481617 0.870073100 0.568099918 0.823585770 0.928676066 0.940514907
#> [91] 0.363261452 0.952356695 0.952356695 0.589618677 0.392481617 0.097280412
#> [97] 0.504664420 0.732469296 0.030692593 0.190009232 0.055891045 0.835191145
#> [103] 0.788984767 0.893534759 0.005533943 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 58 63 101 18 14 15 81 90 30 96 187 177 197
#> 19.34 22.77 9.97 15.21 12.89 22.68 14.06 20.94 17.43 14.54 9.92 12.53 21.60
#> 108 85 14.1 158 86 63.1 66 197.1 140 25 108.1 23 154
#> 18.29 16.44 12.89 20.14 23.81 22.77 22.13 21.60 12.68 6.32 18.29 16.92 12.63
#> 43 55 188 168 57 190 85.1 168.1 10 125 56 100 110
#> 12.10 19.34 16.16 23.72 14.46 20.81 16.44 23.72 10.53 15.65 12.21 16.07 17.56
#> 24 85.2 14.2 183 127 60 140.1 37 13 107 55.1 36 66.1
#> 23.89 16.44 12.89 9.24 3.53 13.15 12.68 12.52 14.34 11.18 19.34 21.19 22.13
#> 110.1 129 177.1 41 117 96.1 90.1 139 139.1 175 175.1 61 190.1
#> 17.56 23.41 12.53 18.02 17.46 14.54 20.94 21.49 21.49 21.91 21.91 10.12 20.81
#> 194 197.2 18.1 155 111 108.2 133 41.1 197.3 181 5 179 134
#> 22.40 21.60 15.21 13.08 17.45 18.29 14.65 18.02 21.60 16.46 16.43 18.63 17.81
#> 60.1 154.1 170 51 40 40.1 23.1 145 57.1 159 16 70 111.1
#> 13.15 12.63 19.54 18.23 18.00 18.00 16.92 10.07 14.46 10.55 8.71 7.38 17.45
#> 77 77.1 13.1 23.2 197.4 18.2 177.2 69 158.1 194.1 10.1 49 187.1
#> 7.27 7.27 14.34 16.92 21.60 15.21 12.53 23.23 20.14 22.40 10.53 12.19 9.92
#> 86.1 182 162 146 65 22 193 82 120 48 19 74 1
#> 23.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 71 143 47 147 75 48.1 53 191 54 135 22.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 172 11 9 31 132 121 84 48.2 82.1 38 38.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.2 163 109 34.1 174.1 118 126 200 11.1 53.1 80 186 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 178 162.1 147.1 119 44 19.1 147.2 54.1 160 47.1 11.2 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.3 21 75.1 67 152.1 34.2 191.1 200.1 138 121.1 102 71.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 137 12 141 48.3 173.1 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[39]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01216238 0.61765817 0.31323193
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.776540616 0.009893608 0.512366729
#> grade_iii, Cure model
#> 1.090539436
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 55 19.34 1 69 0 1
#> 41 18.02 1 40 1 0
#> 77 7.27 1 67 0 1
#> 32 20.90 1 37 1 0
#> 194 22.40 1 38 0 1
#> 125 15.65 1 67 1 0
#> 36 21.19 1 48 0 1
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 150 20.33 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 60 13.15 1 38 1 0
#> 59 10.16 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 26 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 70 7.38 1 30 1 0
#> 111.1 17.45 1 47 0 1
#> 117 17.46 1 26 0 1
#> 79 16.23 1 54 1 0
#> 105 19.75 1 60 0 0
#> 96 14.54 1 33 0 1
#> 177 12.53 1 75 0 0
#> 78 23.88 1 43 0 0
#> 88 18.37 1 47 0 0
#> 169 22.41 1 46 0 0
#> 117.1 17.46 1 26 0 1
#> 117.2 17.46 1 26 0 1
#> 190 20.81 1 42 1 0
#> 69 23.23 1 25 0 1
#> 106 16.67 1 49 1 0
#> 43 12.10 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 150.2 20.33 1 48 0 0
#> 49 12.19 1 48 1 0
#> 79.1 16.23 1 54 1 0
#> 139.1 21.49 1 63 1 0
#> 181 16.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 37 12.52 1 57 1 0
#> 110 17.56 1 65 0 1
#> 181.1 16.46 1 45 0 1
#> 88.1 18.37 1 47 0 0
#> 154 12.63 1 20 1 0
#> 42 12.43 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 140 12.68 1 59 1 0
#> 16 8.71 1 71 0 1
#> 86 23.81 1 58 0 1
#> 42.1 12.43 1 49 0 1
#> 134 17.81 1 47 1 0
#> 153 21.33 1 55 1 0
#> 36.1 21.19 1 48 0 1
#> 114 13.68 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 177.1 12.53 1 75 0 0
#> 111.2 17.45 1 47 0 1
#> 100 16.07 1 60 0 0
#> 128 20.35 1 35 0 1
#> 169.1 22.41 1 46 0 0
#> 139.2 21.49 1 63 1 0
#> 123 13.00 1 44 1 0
#> 192 16.44 1 31 1 0
#> 99.1 21.19 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 133 14.65 1 57 0 0
#> 49.1 12.19 1 48 1 0
#> 177.2 12.53 1 75 0 0
#> 136 21.83 1 43 0 1
#> 60.1 13.15 1 38 1 0
#> 108 18.29 1 39 0 1
#> 92 22.92 1 47 0 1
#> 169.2 22.41 1 46 0 0
#> 8 18.43 1 32 0 0
#> 100.1 16.07 1 60 0 0
#> 76 19.22 1 54 0 1
#> 166 19.98 1 48 0 0
#> 32.1 20.90 1 37 1 0
#> 153.1 21.33 1 55 1 0
#> 77.1 7.27 1 67 0 1
#> 89 11.44 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 107 11.18 1 54 1 0
#> 187 9.92 1 39 1 0
#> 66 22.13 1 53 0 0
#> 60.2 13.15 1 38 1 0
#> 123.1 13.00 1 44 1 0
#> 79.2 16.23 1 54 1 0
#> 108.1 18.29 1 39 0 1
#> 181.2 16.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 167 15.55 1 56 1 0
#> 166.1 19.98 1 48 0 0
#> 32.2 20.90 1 37 1 0
#> 155 13.08 1 26 0 0
#> 128.1 20.35 1 35 0 1
#> 133.1 14.65 1 57 0 0
#> 97.1 19.14 1 65 0 1
#> 128.2 20.35 1 35 0 1
#> 166.2 19.98 1 48 0 0
#> 78.1 23.88 1 43 0 0
#> 76.1 19.22 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 96.1 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 136.1 21.83 1 43 0 1
#> 25 6.32 1 34 1 0
#> 57 14.46 1 45 0 1
#> 162 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 31 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 135.1 24.00 0 58 1 0
#> 17 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 75 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 31.1 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 135.2 24.00 0 58 1 0
#> 64 24.00 0 43 0 0
#> 135.3 24.00 0 58 1 0
#> 162.1 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 135.4 24.00 0 58 1 0
#> 21 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 21.1 24.00 0 47 0 0
#> 65 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 109 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 47 24.00 0 38 0 1
#> 193.1 24.00 0 45 0 1
#> 156 24.00 0 50 1 0
#> 65.1 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 65.2 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 98 24.00 0 34 1 0
#> 172 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 2 24.00 0 9 0 0
#> 64.1 24.00 0 43 0 0
#> 9 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 94.1 24.00 0 51 0 1
#> 115.1 24.00 0 NA 1 0
#> 21.2 24.00 0 47 0 0
#> 112.1 24.00 0 61 0 0
#> 54 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 196.1 24.00 0 19 0 0
#> 84 24.00 0 39 0 1
#> 163 24.00 0 66 0 0
#> 3.1 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 198.1 24.00 0 66 0 1
#> 178 24.00 0 52 1 0
#> 75.2 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 33 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 17.1 24.00 0 38 0 1
#> 200.1 24.00 0 64 0 0
#> 152.1 24.00 0 36 0 1
#> 112.2 24.00 0 61 0 0
#> 94.2 24.00 0 51 0 1
#> 135.5 24.00 0 58 1 0
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 138.1 24.00 0 44 1 0
#> 115.2 24.00 0 NA 1 0
#> 137.1 24.00 0 45 1 0
#> 12.1 24.00 0 63 0 0
#> 119.1 24.00 0 17 0 0
#> 156.1 24.00 0 50 1 0
#> 53.1 24.00 0 32 0 1
#> 67 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 198.2 24.00 0 66 0 1
#> 17.2 24.00 0 38 0 1
#> 162.2 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.777 NA NA NA
#> 2 age, Cure model 0.00989 NA NA NA
#> 3 grade_ii, Cure model 0.512 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0122 NA NA NA
#> 2 grade_ii, Survival model 0.618 NA NA NA
#> 3 grade_iii, Survival model 0.313 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.776541 0.009894 0.512367 1.090539
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 250.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.776540616 0.009893608 0.512366729 1.090539436
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01216238 0.61765817 0.31323193
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7843400 0.6654876 0.7314812 0.9813021 0.5397413 0.3731491 0.8471627
#> [8] 0.5016637 0.4437855 0.7673642 0.6058885 0.6058885 0.8851797 0.6582148
#> [15] 0.8421861 0.8520478 0.9774584 0.7673642 0.7498367 0.8170077 0.6508354
#> [22] 0.8711709 0.9206517 0.1111370 0.7059631 0.3144348 0.7498367 0.7498367
#> [29] 0.5658948 0.2365799 0.7899948 0.9538078 0.5658948 0.6058885 0.9457295
#> [36] 0.8170077 0.4437855 0.7955554 0.5016637 0.9333028 0.7438239 0.7955554
#> [43] 0.7059631 0.9163263 0.9374875 0.2365799 0.9119728 0.9696926 0.2010420
#> [50] 0.9374875 0.7377116 0.4800563 0.5016637 0.9617966 0.9206517 0.7673642
#> [57] 0.8321748 0.5823963 0.3144348 0.4437855 0.9031692 0.8116632 0.5016637
#> [64] 0.8617115 0.9457295 0.9206517 0.4111876 0.8851797 0.7188578 0.2898327
#> [71] 0.3144348 0.6993930 0.8321748 0.6725923 0.6286803 0.5397413 0.4800563
#> [78] 0.9813021 0.9926071 0.9578237 0.9657606 0.3925850 0.8851797 0.9031692
#> [85] 0.8170077 0.7188578 0.7955554 0.6862562 0.8569159 0.6286803 0.5397413
#> [92] 0.8986611 0.5823963 0.8617115 0.6862562 0.5823963 0.6286803 0.1111370
#> [99] 0.6725923 0.9926071 0.8711709 0.9735892 0.4111876 0.9888512 0.8805243
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 23 55 41 77 32 194 125 36 139 111 150 150.1 60
#> 16.92 19.34 18.02 7.27 20.90 22.40 15.65 21.19 21.49 17.45 20.33 20.33 13.15
#> 170 26 6 70 111.1 117 79 105 96 177 78 88 169
#> 19.54 15.77 15.64 7.38 17.45 17.46 16.23 19.75 14.54 12.53 23.88 18.37 22.41
#> 117.1 117.2 190 69 106 43 190.1 150.2 49 79.1 139.1 181 99
#> 17.46 17.46 20.81 23.23 16.67 12.10 20.81 20.33 12.19 16.23 21.49 16.46 21.19
#> 37 110 181.1 88.1 154 42 69.1 140 16 86 42.1 134 153
#> 12.52 17.56 16.46 18.37 12.63 12.43 23.23 12.68 8.71 23.81 12.43 17.81 21.33
#> 36.1 101 177.1 111.2 100 128 169.1 139.2 123 192 99.1 133 49.1
#> 21.19 9.97 12.53 17.45 16.07 20.35 22.41 21.49 13.00 16.44 21.19 14.65 12.19
#> 177.2 136 60.1 108 92 169.2 8 100.1 76 166 32.1 153.1 77.1
#> 12.53 21.83 13.15 18.29 22.92 22.41 18.43 16.07 19.22 19.98 20.90 21.33 7.27
#> 91 107 187 66 60.2 123.1 79.2 108.1 181.2 97 167 166.1 32.2
#> 5.33 11.18 9.92 22.13 13.15 13.00 16.23 18.29 16.46 19.14 15.55 19.98 20.90
#> 155 128.1 133.1 97.1 128.2 166.2 78.1 76.1 91.1 96.1 149 136.1 25
#> 13.08 20.35 14.65 19.14 20.35 19.98 23.88 19.22 5.33 14.54 8.37 21.83 6.32
#> 57 162 135 31 135.1 17 161 193 75 31.1 94 135.2 64
#> 14.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.3 162.1 131 3 112 135.4 21 118 95 196 62 102 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 83 138 151 109 119 47 193.1 156 65.1 142 65.2 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 98 172 53 2 64.1 9 20 200 94.1 21.2 112.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 196.1 84 163 3.1 75.1 176 198.1 178 75.2 87 33 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 200.1 152.1 112.2 94.2 135.5 137 27 35 138.1 137.1 12.1 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 53.1 67 148 198.2 17.2 162.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[40]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00847354 0.05209230 -0.17497931
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.76171785 0.01138337 0.37860406
#> grade_iii, Cure model
#> 1.11539844
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 111 17.45 1 47 0 1
#> 158 20.14 1 74 1 0
#> 171 16.57 1 41 0 1
#> 14 12.89 1 21 0 0
#> 128 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 181 16.46 1 45 0 1
#> 158.1 20.14 1 74 1 0
#> 18 15.21 1 49 1 0
#> 171.1 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 194.1 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 18.1 15.21 1 49 1 0
#> 86 23.81 1 58 0 1
#> 97 19.14 1 65 0 1
#> 179 18.63 1 42 0 0
#> 167 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 50 10.02 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 139 21.49 1 63 1 0
#> 43 12.10 1 61 0 1
#> 177 12.53 1 75 0 0
#> 155.1 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 108 18.29 1 39 0 1
#> 127 3.53 1 62 0 1
#> 195 11.76 1 NA 1 0
#> 158.2 20.14 1 74 1 0
#> 123.1 13.00 1 44 1 0
#> 51 18.23 1 83 0 1
#> 180 14.82 1 37 0 0
#> 18.2 15.21 1 49 1 0
#> 18.3 15.21 1 49 1 0
#> 43.1 12.10 1 61 0 1
#> 89 11.44 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 39 15.59 1 37 0 1
#> 150 20.33 1 48 0 0
#> 8 18.43 1 32 0 0
#> 77 7.27 1 67 0 1
#> 90 20.94 1 50 0 1
#> 69 23.23 1 25 0 1
#> 136 21.83 1 43 0 1
#> 63 22.77 1 31 1 0
#> 166 19.98 1 48 0 0
#> 43.2 12.10 1 61 0 1
#> 52 10.42 1 52 0 1
#> 25 6.32 1 34 1 0
#> 170 19.54 1 43 0 1
#> 177.1 12.53 1 75 0 0
#> 190 20.81 1 42 1 0
#> 32.1 20.90 1 37 1 0
#> 60 13.15 1 38 1 0
#> 154 12.63 1 20 1 0
#> 154.1 12.63 1 20 1 0
#> 40 18.00 1 28 1 0
#> 136.1 21.83 1 43 0 1
#> 92 22.92 1 47 0 1
#> 56 12.21 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 180.1 14.82 1 37 0 0
#> 13 14.34 1 54 0 1
#> 39.1 15.59 1 37 0 1
#> 183 9.24 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 105 19.75 1 60 0 0
#> 139.1 21.49 1 63 1 0
#> 88 18.37 1 47 0 0
#> 136.2 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 18.4 15.21 1 49 1 0
#> 56.1 12.21 1 60 0 0
#> 155.2 13.08 1 26 0 0
#> 57 14.46 1 45 0 1
#> 88.1 18.37 1 47 0 0
#> 40.1 18.00 1 28 1 0
#> 140 12.68 1 59 1 0
#> 69.1 23.23 1 25 0 1
#> 158.3 20.14 1 74 1 0
#> 167.1 15.55 1 56 1 0
#> 32.2 20.90 1 37 1 0
#> 66 22.13 1 53 0 0
#> 29 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 55 19.34 1 69 0 1
#> 149 8.37 1 33 1 0
#> 150.1 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 199 19.81 1 NA 0 1
#> 183.2 9.24 1 67 1 0
#> 6 15.64 1 39 0 0
#> 177.2 12.53 1 75 0 0
#> 96 14.54 1 33 0 1
#> 37 12.52 1 57 1 0
#> 123.2 13.00 1 44 1 0
#> 18.5 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 194.2 22.40 1 38 0 1
#> 36 21.19 1 48 0 1
#> 107 11.18 1 54 1 0
#> 91 5.33 1 61 0 1
#> 105.1 19.75 1 60 0 0
#> 177.3 12.53 1 75 0 0
#> 181.1 16.46 1 45 0 1
#> 23 16.92 1 61 0 0
#> 117 17.46 1 26 0 1
#> 150.2 20.33 1 48 0 0
#> 180.2 14.82 1 37 0 0
#> 59 10.16 1 NA 1 0
#> 12 24.00 0 63 0 0
#> 109 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 33 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 121 24.00 0 57 1 0
#> 3 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 200 24.00 0 64 0 0
#> 1 24.00 0 23 1 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 20 24.00 0 46 1 0
#> 35 24.00 0 51 0 0
#> 1.1 24.00 0 23 1 0
#> 200.1 24.00 0 64 0 0
#> 83 24.00 0 6 0 0
#> 163 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 146 24.00 0 63 1 0
#> 94 24.00 0 51 0 1
#> 196.1 24.00 0 19 0 0
#> 116.1 24.00 0 58 0 1
#> 116.2 24.00 0 58 0 1
#> 122.1 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 38.1 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 73.1 24.00 0 NA 0 1
#> 163.1 24.00 0 66 0 0
#> 73.2 24.00 0 NA 0 1
#> 22.1 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 144 24.00 0 28 0 1
#> 109.2 24.00 0 48 0 0
#> 3.1 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 176 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 44.1 24.00 0 56 0 0
#> 141 24.00 0 44 1 0
#> 38.2 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 152 24.00 0 36 0 1
#> 47.1 24.00 0 38 0 1
#> 162 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 19 24.00 0 57 0 1
#> 185 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 122.2 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 9.1 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 73.3 24.00 0 NA 0 1
#> 7.1 24.00 0 37 1 0
#> 9.2 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 161 24.00 0 45 0 0
#> 131.1 24.00 0 66 0 0
#> 22.2 24.00 0 52 1 0
#> 75.1 24.00 0 21 1 0
#> 174 24.00 0 49 1 0
#> 2 24.00 0 9 0 0
#> 132.1 24.00 0 55 0 0
#> 142 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 103.1 24.00 0 56 1 0
#> 176.1 24.00 0 43 0 1
#> 200.2 24.00 0 64 0 0
#> 98 24.00 0 34 1 0
#> 19.1 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.762 NA NA NA
#> 2 age, Cure model 0.0114 NA NA NA
#> 3 grade_ii, Cure model 0.379 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00847 NA NA NA
#> 2 grade_ii, Survival model 0.0521 NA NA NA
#> 3 grade_iii, Survival model -0.175 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76172 0.01138 0.37860 1.11540
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262
#> Residual Deviance: 252.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76171785 0.01138337 0.37860406 1.11539844
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00847354 0.05209230 -0.17497931
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.16921918 0.57758921 0.40337416 0.60223404 0.82675544 0.36256075
#> [7] 0.26103673 0.62642020 0.40337416 0.68949185 0.60223404 0.80557697
#> [13] 0.16921918 0.78409958 0.68949185 0.04930891 0.49299927 0.50175142
#> [19] 0.66617981 0.61834497 0.31990399 0.27368597 0.90215073 0.85493973
#> [25] 0.78409958 0.02388863 0.53594730 0.99359753 0.40337416 0.80557697
#> [31] 0.54442555 0.73300003 0.68949185 0.68949185 0.90215073 0.58585489
#> [37] 0.65036040 0.37331005 0.51043881 0.97428675 0.30838510 0.08899490
#> [43] 0.22335316 0.13792585 0.43951126 0.90215073 0.93525268 0.98074081
#> [49] 0.46652792 0.85493973 0.35177011 0.31990399 0.77682451 0.84092851
#> [55] 0.84092851 0.55281289 0.22335316 0.12118504 0.88874792 0.46652792
#> [61] 0.73300003 0.76951841 0.65036040 0.94846708 0.94846708 0.44873997
#> [67] 0.27368597 0.51908039 0.22335316 0.15395028 0.68949185 0.88874792
#> [73] 0.78409958 0.76218958 0.51908039 0.55281289 0.83386416 0.08899490
#> [79] 0.40337416 0.66617981 0.31990399 0.20949928 0.68174308 0.07091301
#> [85] 0.48417566 0.96781206 0.37331005 0.92863326 0.94846708 0.64237296
#> [91] 0.85493973 0.75484457 0.88195289 0.80557697 0.68949185 0.94185788
#> [97] 0.16921918 0.29674350 0.92200049 0.98717770 0.44873997 0.85493973
#> [103] 0.62642020 0.59408267 0.56929383 0.37331005 0.73300003 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 194 111 158 171 14 128 197 181 158.1 18 171.1 123 194.1
#> 22.40 17.45 20.14 16.57 12.89 20.35 21.60 16.46 20.14 15.21 16.57 13.00 22.40
#> 155 18.1 86 97 179 167 130 32 139 43 177 155.1 24
#> 13.08 15.21 23.81 19.14 18.63 15.55 16.47 20.90 21.49 12.10 12.53 13.08 23.89
#> 108 127 158.2 123.1 51 180 18.2 18.3 43.1 45 39 150 8
#> 18.29 3.53 20.14 13.00 18.23 14.82 15.21 15.21 12.10 17.42 15.59 20.33 18.43
#> 77 90 69 136 63 166 43.2 52 25 170 177.1 190 32.1
#> 7.27 20.94 23.23 21.83 22.77 19.98 12.10 10.42 6.32 19.54 12.53 20.81 20.90
#> 60 154 154.1 40 136.1 92 56 170.1 180.1 13 39.1 183 183.1
#> 13.15 12.63 12.63 18.00 21.83 22.92 12.21 19.54 14.82 14.34 15.59 9.24 9.24
#> 105 139.1 88 136.2 169 18.4 56.1 155.2 57 88.1 40.1 140 69.1
#> 19.75 21.49 18.37 21.83 22.41 15.21 12.21 13.08 14.46 18.37 18.00 12.68 23.23
#> 158.3 167.1 32.2 66 29 129 55 149 150.1 159 183.2 6 177.2
#> 20.14 15.55 20.90 22.13 15.45 23.41 19.34 8.37 20.33 10.55 9.24 15.64 12.53
#> 96 37 123.2 18.5 101 194.2 36 107 91 105.1 177.3 181.1 23
#> 14.54 12.52 13.00 15.21 9.97 22.40 21.19 11.18 5.33 19.75 12.53 16.46 16.92
#> 117 150.2 180.2 12 109 33 109.1 74 172 71 22 44 75
#> 17.46 20.33 14.82 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 3 38 103 200 1 72 116 20 35 1.1 200.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 47 122 196 146 94 196.1 116.1 116.2 122.1 126 132 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 12.1 163.1 22.1 156 144 109.2 3.1 9 28 176 62 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 141 38.2 119 152 47.1 162 178 84 19 185 11 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 122.2 141.1 9.1 131 7.1 9.2 104 161 131.1 22.2 75.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 132.1 142 191 103.1 176.1 200.2 98 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[41]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0007586918 0.4734692230 0.1612825614
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.94700613 0.01957017 -0.25446870
#> grade_iii, Cure model
#> 0.98941411
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 49 12.19 1 48 1 0
#> 49.1 12.19 1 48 1 0
#> 181 16.46 1 45 0 1
#> 140 12.68 1 59 1 0
#> 58 19.34 1 39 0 0
#> 26 15.77 1 49 0 1
#> 145 10.07 1 65 1 0
#> 6 15.64 1 39 0 0
#> 52 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 68 20.62 1 44 0 0
#> 136.1 21.83 1 43 0 1
#> 149 8.37 1 33 1 0
#> 16 8.71 1 71 0 1
#> 175 21.91 1 43 0 0
#> 181.1 16.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 177 12.53 1 75 0 0
#> 133 14.65 1 57 0 0
#> 40 18.00 1 28 1 0
#> 18 15.21 1 49 1 0
#> 49.2 12.19 1 48 1 0
#> 155 13.08 1 26 0 0
#> 170 19.54 1 43 0 1
#> 129 23.41 1 53 1 0
#> 88 18.37 1 47 0 0
#> 164 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 70 7.38 1 30 1 0
#> 24 23.89 1 38 0 0
#> 150 20.33 1 48 0 0
#> 51 18.23 1 83 0 1
#> 39 15.59 1 37 0 1
#> 90 20.94 1 50 0 1
#> 167 15.55 1 56 1 0
#> 93 10.33 1 52 0 1
#> 111 17.45 1 47 0 1
#> 32 20.90 1 37 1 0
#> 128 20.35 1 35 0 1
#> 154 12.63 1 20 1 0
#> 63 22.77 1 31 1 0
#> 133.1 14.65 1 57 0 0
#> 92 22.92 1 47 0 1
#> 41 18.02 1 40 1 0
#> 68.1 20.62 1 44 0 0
#> 145.1 10.07 1 65 1 0
#> 45.1 17.42 1 54 0 1
#> 81 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 97 19.14 1 65 0 1
#> 106 16.67 1 49 1 0
#> 125 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 37 12.52 1 57 1 0
#> 157 15.10 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 86 23.81 1 58 0 1
#> 30.1 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 108 18.29 1 39 0 1
#> 149.1 8.37 1 33 1 0
#> 69 23.23 1 25 0 1
#> 180 14.82 1 37 0 0
#> 25 6.32 1 34 1 0
#> 159 10.55 1 50 0 1
#> 81.1 14.06 1 34 0 0
#> 128.1 20.35 1 35 0 1
#> 68.2 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 197 21.60 1 69 1 0
#> 30.2 17.43 1 78 0 0
#> 59 10.16 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 127 3.53 1 62 0 1
#> 166 19.98 1 48 0 0
#> 91 5.33 1 61 0 1
#> 153 21.33 1 55 1 0
#> 175.1 21.91 1 43 0 0
#> 24.1 23.89 1 38 0 0
#> 5 16.43 1 51 0 1
#> 66 22.13 1 53 0 0
#> 129.1 23.41 1 53 1 0
#> 51.1 18.23 1 83 0 1
#> 111.1 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 59.1 10.16 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 117 17.46 1 26 0 1
#> 164.1 23.60 1 76 0 1
#> 101.1 9.97 1 10 0 1
#> 91.1 5.33 1 61 0 1
#> 4 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 113 22.86 1 34 0 0
#> 194 22.40 1 38 0 1
#> 108.1 18.29 1 39 0 1
#> 97.1 19.14 1 65 0 1
#> 6.1 15.64 1 39 0 0
#> 106.1 16.67 1 49 1 0
#> 114.1 13.68 1 NA 0 0
#> 105 19.75 1 60 0 0
#> 49.3 12.19 1 48 1 0
#> 39.2 15.59 1 37 0 1
#> 195 11.76 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 36 21.19 1 48 0 1
#> 23 16.92 1 61 0 0
#> 52.1 10.42 1 52 0 1
#> 56.1 12.21 1 60 0 0
#> 4.1 17.64 1 NA 0 1
#> 122 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 121 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 137 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 3.1 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 12 24.00 0 63 0 0
#> 2 24.00 0 9 0 0
#> 83.1 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 137.1 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 22 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 27 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 156 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 83.2 24.00 0 6 0 0
#> 178 24.00 0 52 1 0
#> 1 24.00 0 23 1 0
#> 186 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 72.1 24.00 0 40 0 1
#> 2.1 24.00 0 9 0 0
#> 1.1 24.00 0 23 1 0
#> 148 24.00 0 61 1 0
#> 142 24.00 0 53 0 0
#> 176.1 24.00 0 43 0 1
#> 126.1 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 146 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 173 24.00 0 19 0 1
#> 131 24.00 0 66 0 0
#> 156.1 24.00 0 50 1 0
#> 148.1 24.00 0 61 1 0
#> 33 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 193.1 24.00 0 45 0 1
#> 95 24.00 0 68 0 1
#> 173.1 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 20.1 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 33.1 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 137.2 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 200.1 24.00 0 64 0 0
#> 75 24.00 0 21 1 0
#> 118 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 19 24.00 0 57 0 1
#> 182.1 24.00 0 35 0 0
#> 156.2 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 7 24.00 0 37 1 0
#> 126.2 24.00 0 48 0 0
#> 173.2 24.00 0 19 0 1
#> 33.2 24.00 0 53 0 0
#> 191.1 24.00 0 60 0 1
#> 67 24.00 0 25 0 0
#> 98.1 24.00 0 34 1 0
#> 48 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 48.1 24.00 0 31 1 0
#> 98.2 24.00 0 34 1 0
#> 118.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 21.1 24.00 0 47 0 0
#> 3.3 24.00 0 31 1 0
#> 115.1 24.00 0 NA 1 0
#> 54 24.00 0 53 1 0
#> 200.2 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.947 NA NA NA
#> 2 age, Cure model 0.0196 NA NA NA
#> 3 grade_ii, Cure model -0.254 NA NA NA
#> 4 grade_iii, Cure model 0.989 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000759 NA NA NA
#> 2 grade_ii, Survival model 0.473 NA NA NA
#> 3 grade_iii, Survival model 0.161 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94701 0.01957 -0.25447 0.98941
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 244.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94700613 0.01957017 -0.25446870 0.98941411
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0007586918 0.4734692230 0.1612825614
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.83621923 0.83621923 0.59138777 0.77612275 0.36634510 0.62733983
#> [7] 0.90254555 0.64518218 0.87760362 0.19647287 0.27869752 0.19647287
#> [13] 0.94357543 0.93535680 0.17495034 0.59138777 0.58228392 0.79341325
#> [19] 0.72396951 0.46240568 0.69780529 0.83621923 0.76739763 0.35651213
#> [25] 0.08392530 0.40494733 0.05748742 0.53648520 0.95978207 0.01482519
#> [31] 0.32693648 0.43383527 0.66285042 0.25861298 0.68902740 0.89421234
#> [37] 0.49055114 0.26876047 0.30755871 0.78479568 0.14169382 0.72396951
#> [43] 0.11837591 0.45288917 0.27869752 0.90254555 0.53648520 0.75005042
#> [49] 0.50899143 0.38570332 0.56418242 0.63629389 0.91897550 0.80203600
#> [55] 0.70652320 0.66285042 0.04149520 0.50899143 0.36634510 0.23861532
#> [61] 0.41469467 0.94357543 0.10657631 0.71524488 0.96788078 0.86923899
#> [67] 0.75005042 0.30755871 0.27869752 0.74133125 0.21767905 0.50899143
#> [73] 0.99196399 0.33678398 0.97594142 0.22827670 0.17495034 0.01482519
#> [79] 0.61836884 0.16388295 0.08392530 0.43383527 0.49055114 0.81060920
#> [85] 0.60938086 0.48119520 0.05748742 0.91897550 0.97594142 0.47181152
#> [91] 0.13002121 0.15284521 0.41469467 0.38570332 0.64518218 0.56418242
#> [97] 0.34664180 0.83621923 0.66285042 0.81917044 0.23861532 0.55489357
#> [103] 0.87760362 0.81917044 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 49 49.1 181 140 58 26 145 6 52 136 68 136.1 149
#> 12.19 12.19 16.46 12.68 19.34 15.77 10.07 15.64 10.42 21.83 20.62 21.83 8.37
#> 16 175 181.1 130 177 133 40 18 49.2 155 170 129 88
#> 8.71 21.91 16.46 16.47 12.53 14.65 18.00 15.21 12.19 13.08 19.54 23.41 18.37
#> 164 45 70 24 150 51 39 90 167 93 111 32 128
#> 23.60 17.42 7.38 23.89 20.33 18.23 15.59 20.94 15.55 10.33 17.45 20.90 20.35
#> 154 63 133.1 92 41 68.1 145.1 45.1 81 30 97 106 125
#> 12.63 22.77 14.65 22.92 18.02 20.62 10.07 17.42 14.06 17.43 19.14 16.67 15.65
#> 101 37 157 39.1 86 30.1 55 99 108 149.1 69 180 25
#> 9.97 12.52 15.10 15.59 23.81 17.43 19.34 21.19 18.29 8.37 23.23 14.82 6.32
#> 159 81.1 128.1 68.2 13 197 30.2 127 166 91 153 175.1 24.1
#> 10.55 14.06 20.35 20.62 14.34 21.60 17.43 3.53 19.98 5.33 21.33 21.91 23.89
#> 5 66 129.1 51.1 111.1 42 192 117 164.1 101.1 91.1 110 113
#> 16.43 22.13 23.41 18.23 17.45 12.43 16.44 17.46 23.60 9.97 5.33 17.56 22.86
#> 194 108.1 97.1 6.1 106.1 105 49.3 39.2 56 36 23 52.1 56.1
#> 22.40 18.29 19.14 15.64 16.67 19.75 12.19 15.59 12.21 21.19 16.92 10.42 12.21
#> 122 83 121 28 3 182 137 135 176 112 3.1 3.2 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 2 83.1 64 126 137.1 163 9 64.1 22 94 27 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 193 83.2 178 1 186 20 72.1 2.1 1.1 148 142 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.1 74 146 151 173 131 156.1 148.1 33 131.1 198 193.1 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 147 20.1 200 33.1 191 137.2 53 200.1 75 118 82 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 156.2 34 7 126.2 173.2 33.2 191.1 67 98.1 48 38 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 98.2 118.1 31 21.1 3.3 54 200.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[42]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004508687 0.364469861 0.212310945
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.526157388 -0.000614379 0.590330703
#> grade_iii, Cure model
#> 1.572347964
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 93 10.33 1 52 0 1
#> 55 19.34 1 69 0 1
#> 52 10.42 1 52 0 1
#> 39 15.59 1 37 0 1
#> 145 10.07 1 65 1 0
#> 189 10.51 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 101 9.97 1 10 0 1
#> 90 20.94 1 50 0 1
#> 14 12.89 1 21 0 0
#> 26 15.77 1 49 0 1
#> 8 18.43 1 32 0 0
#> 192 16.44 1 31 1 0
#> 63 22.77 1 31 1 0
#> 91 5.33 1 61 0 1
#> 69 23.23 1 25 0 1
#> 180 14.82 1 37 0 0
#> 139 21.49 1 63 1 0
#> 170 19.54 1 43 0 1
#> 123 13.00 1 44 1 0
#> 159 10.55 1 50 0 1
#> 13 14.34 1 54 0 1
#> 60 13.15 1 38 1 0
#> 6 15.64 1 39 0 0
#> 55.1 19.34 1 69 0 1
#> 92 22.92 1 47 0 1
#> 159.1 10.55 1 50 0 1
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 81 14.06 1 34 0 0
#> 171 16.57 1 41 0 1
#> 177 12.53 1 75 0 0
#> 42 12.43 1 49 0 1
#> 15 22.68 1 48 0 0
#> 149 8.37 1 33 1 0
#> 114 13.68 1 NA 0 0
#> 81.1 14.06 1 34 0 0
#> 153 21.33 1 55 1 0
#> 77 7.27 1 67 0 1
#> 55.2 19.34 1 69 0 1
#> 8.1 18.43 1 32 0 0
#> 171.1 16.57 1 41 0 1
#> 125 15.65 1 67 1 0
#> 171.2 16.57 1 41 0 1
#> 59 10.16 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 125.1 15.65 1 67 1 0
#> 171.3 16.57 1 41 0 1
#> 13.1 14.34 1 54 0 1
#> 57 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 70 7.38 1 30 1 0
#> 128 20.35 1 35 0 1
#> 125.2 15.65 1 67 1 0
#> 77.1 7.27 1 67 0 1
#> 61 10.12 1 36 0 1
#> 92.1 22.92 1 47 0 1
#> 183 9.24 1 67 1 0
#> 49 12.19 1 48 1 0
#> 50 10.02 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 60.1 13.15 1 38 1 0
#> 199 19.81 1 NA 0 1
#> 13.2 14.34 1 54 0 1
#> 128.1 20.35 1 35 0 1
#> 183.1 9.24 1 67 1 0
#> 134.1 17.81 1 47 1 0
#> 40 18.00 1 28 1 0
#> 86 23.81 1 58 0 1
#> 169 22.41 1 46 0 0
#> 113 22.86 1 34 0 0
#> 24 23.89 1 38 0 0
#> 164 23.60 1 76 0 1
#> 150 20.33 1 48 0 0
#> 127 3.53 1 62 0 1
#> 59.1 10.16 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 68 20.62 1 44 0 0
#> 49.1 12.19 1 48 1 0
#> 97 19.14 1 65 0 1
#> 93.1 10.33 1 52 0 1
#> 14.1 12.89 1 21 0 0
#> 68.1 20.62 1 44 0 0
#> 52.1 10.42 1 52 0 1
#> 93.2 10.33 1 52 0 1
#> 128.2 20.35 1 35 0 1
#> 66 22.13 1 53 0 0
#> 106 16.67 1 49 1 0
#> 157 15.10 1 47 0 0
#> 190.2 20.81 1 42 1 0
#> 199.1 19.81 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 45 17.42 1 54 0 1
#> 149.1 8.37 1 33 1 0
#> 59.2 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 10 10.53 1 34 0 0
#> 125.3 15.65 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 108.1 18.29 1 39 0 1
#> 197 21.60 1 69 1 0
#> 139.1 21.49 1 63 1 0
#> 194 22.40 1 38 0 1
#> 14.2 12.89 1 21 0 0
#> 59.3 10.16 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 85 16.44 1 36 0 0
#> 137 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 28 24.00 0 67 1 0
#> 73 24.00 0 NA 0 1
#> 9 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 20 24.00 0 46 1 0
#> 126 24.00 0 48 0 0
#> 121 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 132 24.00 0 55 0 0
#> 120 24.00 0 68 0 1
#> 11 24.00 0 42 0 1
#> 198 24.00 0 66 0 1
#> 112 24.00 0 61 0 0
#> 95 24.00 0 68 0 1
#> 9.1 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 109 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 71 24.00 0 51 0 0
#> 109.1 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 132.2 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 126.1 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 131 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 143 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 147 24.00 0 76 1 0
#> 198.1 24.00 0 66 0 1
#> 131.1 24.00 0 66 0 0
#> 121.1 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 64.1 24.00 0 43 0 0
#> 144.1 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 162 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 109.2 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 67 24.00 0 25 0 0
#> 1 24.00 0 23 1 0
#> 165 24.00 0 47 0 0
#> 109.3 24.00 0 48 0 0
#> 109.4 24.00 0 48 0 0
#> 82 24.00 0 34 0 0
#> 156.1 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 185 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 185.1 24.00 0 44 1 0
#> 132.3 24.00 0 55 0 0
#> 144.2 24.00 0 28 0 1
#> 182 24.00 0 35 0 0
#> 160 24.00 0 31 1 0
#> 121.2 24.00 0 57 1 0
#> 162.1 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 160.1 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 11.1 24.00 0 42 0 1
#> 22 24.00 0 52 1 0
#> 64.2 24.00 0 43 0 0
#> 20.1 24.00 0 46 1 0
#> 162.2 24.00 0 51 0 0
#> 144.3 24.00 0 28 0 1
#> 67.1 24.00 0 25 0 0
#> 119.1 24.00 0 17 0 0
#> 185.2 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 182.1 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.526 NA NA NA
#> 2 age, Cure model -0.000614 NA NA NA
#> 3 grade_ii, Cure model 0.590 NA NA NA
#> 4 grade_iii, Cure model 1.57 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00451 NA NA NA
#> 2 grade_ii, Survival model 0.364 NA NA NA
#> 3 grade_iii, Survival model 0.212 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5261574 -0.0006144 0.5903307 1.5723480
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 238.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.526157388 -0.000614379 0.590330703 1.572347964
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004508687 0.364469861 0.212310945
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.841354335 0.285472610 0.821420966 0.582631651 0.881123955 0.424956191
#> [7] 0.891139776 0.167851640 0.721917398 0.523945345 0.324995333 0.504134168
#> [13] 0.074527395 0.980191309 0.034798061 0.602574860 0.137266073 0.275423751
#> [19] 0.711942469 0.791511891 0.632591297 0.682115240 0.572668151 0.285472610
#> [25] 0.045345840 0.791511891 0.345126980 0.901135151 0.662164752 0.455232640
#> [31] 0.751540167 0.761585453 0.084601056 0.930915494 0.662164752 0.157481611
#> [37] 0.960501106 0.285472610 0.324995333 0.455232640 0.533948027 0.455232640
#> [43] 0.375325899 0.533948027 0.455232640 0.632591297 0.622590403 0.395101508
#> [49] 0.950622509 0.226485705 0.533948027 0.960501106 0.871099701 0.045345840
#> [55] 0.911107563 0.771631878 0.612587991 0.682115240 0.632591297 0.226485705
#> [61] 0.911107563 0.375325899 0.365215444 0.013709797 0.094914906 0.064101485
#> [67] 0.004183835 0.023935347 0.255300567 0.990092433 0.265368107 0.178230231
#> [73] 0.178230231 0.206702990 0.771631878 0.314854548 0.841354335 0.721917398
#> [79] 0.206702990 0.821420966 0.841354335 0.226485705 0.115930190 0.445161609
#> [85] 0.592587233 0.178230231 0.405135980 0.435055296 0.930915494 0.494109036
#> [91] 0.811398442 0.533948027 0.405135980 0.345126980 0.126622486 0.137266073
#> [97] 0.105443996 0.721917398 0.701942228 0.504134168 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 93 55 52 39 145 30 101 90 14 26 8 192 63
#> 10.33 19.34 10.42 15.59 10.07 17.43 9.97 20.94 12.89 15.77 18.43 16.44 22.77
#> 91 69 180 139 170 123 159 13 60 6 55.1 92 159.1
#> 5.33 23.23 14.82 21.49 19.54 13.00 10.55 14.34 13.15 15.64 19.34 22.92 10.55
#> 108 187 81 171 177 42 15 149 81.1 153 77 55.2 8.1
#> 18.29 9.92 14.06 16.57 12.53 12.43 22.68 8.37 14.06 21.33 7.27 19.34 18.43
#> 171.1 125 171.2 134 125.1 171.3 13.1 57 110 70 128 125.2 77.1
#> 16.57 15.65 16.57 17.81 15.65 16.57 14.34 14.46 17.56 7.38 20.35 15.65 7.27
#> 61 92.1 183 49 96 60.1 13.2 128.1 183.1 134.1 40 86 169
#> 10.12 22.92 9.24 12.19 14.54 13.15 14.34 20.35 9.24 17.81 18.00 23.81 22.41
#> 113 24 164 150 127 158 190 190.1 68 49.1 97 93.1 14.1
#> 22.86 23.89 23.60 20.33 3.53 20.14 20.81 20.81 20.62 12.19 19.14 10.33 12.89
#> 68.1 52.1 93.2 128.2 66 106 157 190.2 111 45 149.1 130 10
#> 20.62 10.42 10.33 20.35 22.13 16.67 15.10 20.81 17.45 17.42 8.37 16.47 10.53
#> 125.3 111.1 108.1 197 139.1 194 14.2 155 85 137 151 28 9
#> 15.65 17.45 18.29 21.60 21.49 22.40 12.89 13.08 16.44 24.00 24.00 24.00 24.00
#> 64 20 126 121 47 144 132 120 11 198 112 95 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 109 71 109.1 87 132.2 193 126.1 156 186 103 131 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 53 147 198.1 131.1 121.1 47.1 64.1 144.1 33 119 162 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.2 186.1 67 1 165 109.3 109.4 82 156.1 118 146 44 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 185 174 185.1 132.3 144.2 182 160 121.2 162.1 38 82.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 74 80 122 176 148 11.1 22 64.2 20.1 162.2 144.3 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 185.2 163 182.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[43]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001549032 0.415251798 0.398173490
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.873558055 0.008367851 0.281030945
#> grade_iii, Cure model
#> 1.574944541
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 8 18.43 1 32 0 0
#> 175 21.91 1 43 0 0
#> 136 21.83 1 43 0 1
#> 180 14.82 1 37 0 0
#> 32 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 181 16.46 1 45 0 1
#> 39 15.59 1 37 0 1
#> 93 10.33 1 52 0 1
#> 190 20.81 1 42 1 0
#> 123 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 195 11.76 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 4.1 17.64 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 113 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 37 12.52 1 57 1 0
#> 108.1 18.29 1 39 0 1
#> 61 10.12 1 36 0 1
#> 100 16.07 1 60 0 0
#> 129 23.41 1 53 1 0
#> 194 22.40 1 38 0 1
#> 37.1 12.52 1 57 1 0
#> 187 9.92 1 39 1 0
#> 139 21.49 1 63 1 0
#> 89 11.44 1 NA 0 0
#> 150 20.33 1 48 0 0
#> 197 21.60 1 69 1 0
#> 195.1 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 179 18.63 1 42 0 0
#> 78 23.88 1 43 0 0
#> 159 10.55 1 50 0 1
#> 68 20.62 1 44 0 0
#> 188 16.16 1 46 0 1
#> 41 18.02 1 40 1 0
#> 114 13.68 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 114.1 13.68 1 NA 0 0
#> 8.1 18.43 1 32 0 0
#> 101 9.97 1 10 0 1
#> 60 13.15 1 38 1 0
#> 90 20.94 1 50 0 1
#> 16.1 8.71 1 71 0 1
#> 124 9.73 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 133 14.65 1 57 0 0
#> 25 6.32 1 34 1 0
#> 114.2 13.68 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 107 11.18 1 54 1 0
#> 117 17.46 1 26 0 1
#> 85 16.44 1 36 0 0
#> 37.2 12.52 1 57 1 0
#> 195.2 11.76 1 NA 1 0
#> 108.2 18.29 1 39 0 1
#> 124.1 9.73 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 26 15.77 1 49 0 1
#> 63 22.77 1 31 1 0
#> 55.1 19.34 1 69 0 1
#> 166 19.98 1 48 0 0
#> 192 16.44 1 31 1 0
#> 57 14.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 124.2 9.73 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 194.1 22.40 1 38 0 1
#> 134 17.81 1 47 1 0
#> 56 12.21 1 60 0 0
#> 81 14.06 1 34 0 0
#> 23 16.92 1 61 0 0
#> 124.3 9.73 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 108.3 18.29 1 39 0 1
#> 15 22.68 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 93.1 10.33 1 52 0 1
#> 90.1 20.94 1 50 0 1
#> 43 12.10 1 61 0 1
#> 76.1 19.22 1 54 0 1
#> 105 19.75 1 60 0 0
#> 15.1 22.68 1 48 0 0
#> 130 16.47 1 53 0 1
#> 51.1 18.23 1 83 0 1
#> 76.2 19.22 1 54 0 1
#> 93.2 10.33 1 52 0 1
#> 60.1 13.15 1 38 1 0
#> 110 17.56 1 65 0 1
#> 134.1 17.81 1 47 1 0
#> 5 16.43 1 51 0 1
#> 70 7.38 1 30 1 0
#> 25.1 6.32 1 34 1 0
#> 77.1 7.27 1 67 0 1
#> 91 5.33 1 61 0 1
#> 107.1 11.18 1 54 1 0
#> 8.2 18.43 1 32 0 0
#> 199 19.81 1 NA 0 1
#> 130.1 16.47 1 53 0 1
#> 188.1 16.16 1 46 0 1
#> 76.3 19.22 1 54 0 1
#> 25.2 6.32 1 34 1 0
#> 188.2 16.16 1 46 0 1
#> 52 10.42 1 52 0 1
#> 110.1 17.56 1 65 0 1
#> 36 21.19 1 48 0 1
#> 88 18.37 1 47 0 0
#> 92 22.92 1 47 0 1
#> 86 23.81 1 58 0 1
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 131 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 9 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 19 24.00 0 57 0 1
#> 112 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 9.1 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 64 24.00 0 43 0 0
#> 120 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 116 24.00 0 58 0 1
#> 172 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 118 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 11.1 24.00 0 42 0 1
#> 121 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 174.1 24.00 0 49 1 0
#> 7.1 24.00 0 37 1 0
#> 21 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 182.1 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 104.1 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 9.2 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 162.1 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 65 24.00 0 57 1 0
#> 2 24.00 0 9 0 0
#> 84 24.00 0 39 0 1
#> 83 24.00 0 6 0 0
#> 151.1 24.00 0 42 0 0
#> 163.1 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 31 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 122.2 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 193 24.00 0 45 0 1
#> 44.1 24.00 0 56 0 0
#> 118.1 24.00 0 44 1 0
#> 9.3 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 44.2 24.00 0 56 0 0
#> 2.1 24.00 0 9 0 0
#> 143.1 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 126.1 24.00 0 48 0 0
#> 118.2 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 163.2 24.00 0 66 0 0
#> 163.3 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 143.2 24.00 0 51 0 0
#> 65.1 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 82 24.00 0 34 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.874 NA NA NA
#> 2 age, Cure model 0.00837 NA NA NA
#> 3 grade_ii, Cure model 0.281 NA NA NA
#> 4 grade_iii, Cure model 1.57 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00155 NA NA NA
#> 2 grade_ii, Survival model 0.415 NA NA NA
#> 3 grade_iii, Survival model 0.398 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.873558 0.008368 0.281031 1.574945
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 252.8
#> Residual Deviance: 231.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.873558055 0.008367851 0.281030945 1.574944541
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001549032 0.415251798 0.398173490
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.48996323 0.21705929 0.23205494 0.75027799 0.32142657 0.56456294
#> [7] 0.66909343 0.74231069 0.88775728 0.33310150 0.79753510 0.52829433
#> [13] 0.93081642 0.35593092 0.12039120 0.80529275 0.82070107 0.52829433
#> [19] 0.90929588 0.72622336 0.08081919 0.18797133 0.82070107 0.92367506
#> [25] 0.27251608 0.36712719 0.24649884 0.41105365 0.48020084 0.02188940
#> [31] 0.87302192 0.34452953 0.70225462 0.58259015 0.44227581 0.48996323
#> [37] 0.91649992 0.78200182 0.29799631 0.93081642 0.60911627 0.75824030
#> [43] 0.96583098 0.37829719 0.85823533 0.63513504 0.67747453 0.82070107
#> [49] 0.52829433 0.42177720 0.73429374 0.13888487 0.42177720 0.38924144
#> [55] 0.67747453 0.76619490 0.99317977 0.81300140 0.18797133 0.59158877
#> [61] 0.84317393 0.77410054 0.64372899 0.95193999 0.52829433 0.15603767
#> [67] 0.24649884 0.88775728 0.29799631 0.85072585 0.44227581 0.40016201
#> [73] 0.15603767 0.65231159 0.56456294 0.44227581 0.88775728 0.78200182
#> [79] 0.61793625 0.59158877 0.69400169 0.94490177 0.96583098 0.95193999
#> [85] 0.98632948 0.85823533 0.48996323 0.65231159 0.70225462 0.44227581
#> [91] 0.96583098 0.70225462 0.88040853 0.61793625 0.28542784 0.51858602
#> [97] 0.10174871 0.05578829 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 8 175 136 180 32 51 181 39 93 190 123 108 16
#> 18.43 21.91 21.83 14.82 20.90 18.23 16.46 15.59 10.33 20.81 13.00 18.29 8.71
#> 128 113 140 37 108.1 61 100 129 194 37.1 187 139 150
#> 20.35 22.86 12.68 12.52 18.29 10.12 16.07 23.41 22.40 12.52 9.92 21.49 20.33
#> 197 170 179 78 159 68 188 41 76 8.1 101 60 90
#> 21.60 19.54 18.63 23.88 10.55 20.62 16.16 18.02 19.22 18.43 9.97 13.15 20.94
#> 16.1 184 133 25 158 107 117 85 37.2 108.2 55 26 63
#> 8.71 17.77 14.65 6.32 20.14 11.18 17.46 16.44 12.52 18.29 19.34 15.77 22.77
#> 55.1 166 192 57 127 177 194.1 134 56 81 23 77 108.3
#> 19.34 19.98 16.44 14.46 3.53 12.53 22.40 17.81 12.21 14.06 16.92 7.27 18.29
#> 15 197.1 93.1 90.1 43 76.1 105 15.1 130 51.1 76.2 93.2 60.1
#> 22.68 21.60 10.33 20.94 12.10 19.22 19.75 22.68 16.47 18.23 19.22 10.33 13.15
#> 110 134.1 5 70 25.1 77.1 91 107.1 8.2 130.1 188.1 76.3 25.2
#> 17.56 17.81 16.43 7.38 6.32 7.27 5.33 11.18 18.43 16.47 16.16 19.22 6.32
#> 188.2 52 110.1 36 88 92 86 122 104 11 131 151 9
#> 16.16 10.42 17.56 21.19 18.37 22.92 23.81 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 47 87 19 112 3 174 160 163 94 9.1 94.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 178 116 172 118 162 182 11.1 121 54 174.1 7.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 146 148 182.1 165 104.1 9.2 122.1 38 152 162.1 126 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 2 84 83 151.1 163.1 176 28 31 22 143 122.2 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 160.1 44 193 44.1 118.1 9.3 109 121.1 44.2 2.1 143.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 126.1 118.2 146.1 35 80 163.2 163.3 165.1 143.2 65.1 138 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[44]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008207378 0.660766570 0.252837131
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.310423097 0.003764411 0.220584127
#> grade_iii, Cure model
#> 0.843922592
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 14 12.89 1 21 0 0
#> 197 21.60 1 69 1 0
#> 63 22.77 1 31 1 0
#> 69 23.23 1 25 0 1
#> 18 15.21 1 49 1 0
#> 111 17.45 1 47 0 1
#> 106 16.67 1 49 1 0
#> 58 19.34 1 39 0 0
#> 150 20.33 1 48 0 0
#> 66 22.13 1 53 0 0
#> 180 14.82 1 37 0 0
#> 45 17.42 1 54 0 1
#> 167 15.55 1 56 1 0
#> 25 6.32 1 34 1 0
#> 189 10.51 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 167.1 15.55 1 56 1 0
#> 77 7.27 1 67 0 1
#> 6 15.64 1 39 0 0
#> 169 22.41 1 46 0 0
#> 105 19.75 1 60 0 0
#> 179 18.63 1 42 0 0
#> 39 15.59 1 37 0 1
#> 180.1 14.82 1 37 0 0
#> 52 10.42 1 52 0 1
#> 37 12.52 1 57 1 0
#> 51 18.23 1 83 0 1
#> 179.1 18.63 1 42 0 0
#> 180.2 14.82 1 37 0 0
#> 29 15.45 1 68 1 0
#> 192 16.44 1 31 1 0
#> 49 12.19 1 48 1 0
#> 23 16.92 1 61 0 0
#> 168 23.72 1 70 0 0
#> 55 19.34 1 69 0 1
#> 63.1 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 149 8.37 1 33 1 0
#> 23.1 16.92 1 61 0 0
#> 133 14.65 1 57 0 0
#> 18.1 15.21 1 49 1 0
#> 49.1 12.19 1 48 1 0
#> 86 23.81 1 58 0 1
#> 91 5.33 1 61 0 1
#> 180.3 14.82 1 37 0 0
#> 194 22.40 1 38 0 1
#> 59 10.16 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 49.2 12.19 1 48 1 0
#> 45.1 17.42 1 54 0 1
#> 133.1 14.65 1 57 0 0
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 168.1 23.72 1 70 0 0
#> 100 16.07 1 60 0 0
#> 168.2 23.72 1 70 0 0
#> 170 19.54 1 43 0 1
#> 114 13.68 1 NA 0 0
#> 29.1 15.45 1 68 1 0
#> 171 16.57 1 41 0 1
#> 153 21.33 1 55 1 0
#> 192.1 16.44 1 31 1 0
#> 10 10.53 1 34 0 0
#> 49.3 12.19 1 48 1 0
#> 50 10.02 1 NA 1 0
#> 168.3 23.72 1 70 0 0
#> 29.2 15.45 1 68 1 0
#> 39.1 15.59 1 37 0 1
#> 51.1 18.23 1 83 0 1
#> 114.1 13.68 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 153.1 21.33 1 55 1 0
#> 179.2 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 113 22.86 1 34 0 0
#> 110 17.56 1 65 0 1
#> 10.1 10.53 1 34 0 0
#> 10.2 10.53 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 113.1 22.86 1 34 0 0
#> 25.1 6.32 1 34 1 0
#> 50.1 10.02 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 113.2 22.86 1 34 0 0
#> 145 10.07 1 65 1 0
#> 26.1 15.77 1 49 0 1
#> 184.1 17.77 1 38 0 0
#> 175 21.91 1 43 0 0
#> 123 13.00 1 44 1 0
#> 37.1 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 150.1 20.33 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 125 15.65 1 67 1 0
#> 136 21.83 1 43 0 1
#> 110.1 17.56 1 65 0 1
#> 93.1 10.33 1 52 0 1
#> 49.4 12.19 1 48 1 0
#> 79 16.23 1 54 1 0
#> 189.1 10.51 1 NA 1 0
#> 26.2 15.77 1 49 0 1
#> 189.2 10.51 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 61 10.12 1 36 0 1
#> 10.3 10.53 1 34 0 0
#> 32 20.90 1 37 1 0
#> 155 13.08 1 26 0 0
#> 110.2 17.56 1 65 0 1
#> 108 18.29 1 39 0 1
#> 127 3.53 1 62 0 1
#> 108.1 18.29 1 39 0 1
#> 120 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 200 24.00 0 64 0 0
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 161 24.00 0 45 0 0
#> 46 24.00 0 71 0 0
#> 1.1 24.00 0 23 1 0
#> 46.1 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 185.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 1.2 24.00 0 23 1 0
#> 46.2 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 118.1 24.00 0 44 1 0
#> 118.2 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 102 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 38 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 3.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 196.1 24.00 0 19 0 0
#> 156 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 161.1 24.00 0 45 0 0
#> 161.2 24.00 0 45 0 0
#> 138 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 46.3 24.00 0 71 0 0
#> 176.1 24.00 0 43 0 1
#> 151.1 24.00 0 42 0 0
#> 9.1 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 31 24.00 0 36 0 1
#> 103.1 24.00 0 56 1 0
#> 28 24.00 0 67 1 0
#> 46.4 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 162.1 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 103.2 24.00 0 56 1 0
#> 48 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 28.1 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 71 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 146.2 24.00 0 63 1 0
#> 64.2 24.00 0 43 0 0
#> 116.1 24.00 0 58 0 1
#> 34.1 24.00 0 36 0 0
#> 7 24.00 0 37 1 0
#> 116.2 24.00 0 58 0 1
#> 151.2 24.00 0 42 0 0
#> 163 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 17.1 24.00 0 38 0 1
#> 200.1 24.00 0 64 0 0
#> 47 24.00 0 38 0 1
#> 71.1 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 62.1 24.00 0 71 0 0
#> 191.1 24.00 0 60 0 1
#> 73 24.00 0 NA 0 1
#> 163.1 24.00 0 66 0 0
#> 64.3 24.00 0 43 0 0
#> 3.2 24.00 0 31 1 0
#> 28.2 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.310 NA NA NA
#> 2 age, Cure model 0.00376 NA NA NA
#> 3 grade_ii, Cure model 0.221 NA NA NA
#> 4 grade_iii, Cure model 0.844 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00821 NA NA NA
#> 2 grade_ii, Survival model 0.661 NA NA NA
#> 3 grade_iii, Survival model 0.253 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.310423 0.003764 0.220584 0.843923
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 254.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.310423097 0.003764411 0.220584127 0.843922592
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008207378 0.660766570 0.252837131
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.752340114 0.741638354 0.142984969 0.078705162 0.033343192 0.636926130
#> [7] 0.394806363 0.447727521 0.235458669 0.198232650 0.114036715 0.657605319
#> [13] 0.405342400 0.584860062 0.958719646 0.042551530 0.584860062 0.948284743
#> [19] 0.553016703 0.095665929 0.216467416 0.264291356 0.563685316 0.657605319
#> [25] 0.875154607 0.762944859 0.313337533 0.264291356 0.657605319 0.605865462
#> [31] 0.469256375 0.783883971 0.426327452 0.008990621 0.235458669 0.078705162
#> [37] 0.161615223 0.937879268 0.426327452 0.698984890 0.636926130 0.783883971
#> [43] 0.002575704 0.979269115 0.657605319 0.104828006 0.783883971 0.405342400
#> [49] 0.698984890 0.885602405 0.333660395 0.008990621 0.500556796 0.008990621
#> [55] 0.225944014 0.605865462 0.458481800 0.171128348 0.469256375 0.834182545
#> [61] 0.783883971 0.008990621 0.605865462 0.563685316 0.313337533 0.171128348
#> [67] 0.264291356 0.343812316 0.052022250 0.364133434 0.834182545 0.834182545
#> [73] 0.052022250 0.958719646 0.511115105 0.052022250 0.916943780 0.511115105
#> [79] 0.343812316 0.123515697 0.730960989 0.762944859 0.254513760 0.198232650
#> [85] 0.142984969 0.542404175 0.133216318 0.364133434 0.885602405 0.783883971
#> [91] 0.490084390 0.511115105 0.927418450 0.906452844 0.834182545 0.189173791
#> [97] 0.720228857 0.364133434 0.293464082 0.989622296 0.293464082 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 154 14 197 63 69 18 111 106 58 150 66 180 45
#> 12.63 12.89 21.60 22.77 23.23 15.21 17.45 16.67 19.34 20.33 22.13 14.82 17.42
#> 167 25 92 167.1 77 6 169 105 179 39 180.1 52 37
#> 15.55 6.32 22.92 15.55 7.27 15.64 22.41 19.75 18.63 15.59 14.82 10.42 12.52
#> 51 179.1 180.2 29 192 49 23 168 55 63.1 139 149 23.1
#> 18.23 18.63 14.82 15.45 16.44 12.19 16.92 23.72 19.34 22.77 21.49 8.37 16.92
#> 133 18.1 49.1 86 91 180.3 194 49.2 45.1 133.1 93 40 168.1
#> 14.65 15.21 12.19 23.81 5.33 14.82 22.40 12.19 17.42 14.65 10.33 18.00 23.72
#> 100 168.2 170 29.1 171 153 192.1 10 49.3 168.3 29.2 39.1 51.1
#> 16.07 23.72 19.54 15.45 16.57 21.33 16.44 10.53 12.19 23.72 15.45 15.59 18.23
#> 153.1 179.2 184 113 110 10.1 10.2 113.1 25.1 26 113.2 145 26.1
#> 21.33 18.63 17.77 22.86 17.56 10.53 10.53 22.86 6.32 15.77 22.86 10.07 15.77
#> 184.1 175 123 37.1 76 150.1 197.1 125 136 110.1 93.1 49.4 79
#> 17.77 21.91 13.00 12.52 19.22 20.33 21.60 15.65 21.83 17.56 10.33 12.19 16.23
#> 26.2 183 61 10.3 32 155 110.2 108 127 108.1 120 27 182
#> 15.77 9.24 10.12 10.53 20.90 13.08 17.56 18.29 3.53 18.29 24.00 24.00 24.00
#> 146 185 19 200 103 9 146.1 17 54 34 1 161 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 46.1 118 185.1 132 1.2 46.2 3 118.1 118.2 143 196 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 102 2 38 64.1 151 3.1 162 178 196.1 156 191 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 161.2 138 172 46.3 176.1 151.1 9.1 2.1 31 103.1 28 46.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 162.1 112 103.2 48 178.1 28.1 173 71 142 146.2 64.2 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 7 116.2 151.2 163 137 95 17.1 200.1 47 71.1 143.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 191.1 163.1 64.3 3.2 28.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[45]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001545186 1.119514717 0.731444209
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.62171195 0.02177092 -0.71484163
#> grade_iii, Cure model
#> 0.15491864
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 125 15.65 1 67 1 0
#> 127 3.53 1 62 0 1
#> 169 22.41 1 46 0 0
#> 168 23.72 1 70 0 0
#> 124 9.73 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 168.1 23.72 1 70 0 0
#> 153 21.33 1 55 1 0
#> 66 22.13 1 53 0 0
#> 181 16.46 1 45 0 1
#> 171 16.57 1 41 0 1
#> 128 20.35 1 35 0 1
#> 127.1 3.53 1 62 0 1
#> 79 16.23 1 54 1 0
#> 150 20.33 1 48 0 0
#> 105 19.75 1 60 0 0
#> 170 19.54 1 43 0 1
#> 92 22.92 1 47 0 1
#> 32 20.90 1 37 1 0
#> 157 15.10 1 47 0 0
#> 187 9.92 1 39 1 0
#> 96 14.54 1 33 0 1
#> 77 7.27 1 67 0 1
#> 167 15.55 1 56 1 0
#> 56 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 78 23.88 1 43 0 0
#> 97 19.14 1 65 0 1
#> 155 13.08 1 26 0 0
#> 26 15.77 1 49 0 1
#> 101 9.97 1 10 0 1
#> 8 18.43 1 32 0 0
#> 105.1 19.75 1 60 0 0
#> 130 16.47 1 53 0 1
#> 15 22.68 1 48 0 0
#> 15.1 22.68 1 48 0 0
#> 37 12.52 1 57 1 0
#> 189 10.51 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 39 15.59 1 37 0 1
#> 89 11.44 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 39.1 15.59 1 37 0 1
#> 175 21.91 1 43 0 0
#> 123 13.00 1 44 1 0
#> 6 15.64 1 39 0 0
#> 97.1 19.14 1 65 0 1
#> 128.1 20.35 1 35 0 1
#> 167.1 15.55 1 56 1 0
#> 37.1 12.52 1 57 1 0
#> 170.1 19.54 1 43 0 1
#> 66.1 22.13 1 53 0 0
#> 60 13.15 1 38 1 0
#> 30 17.43 1 78 0 0
#> 69 23.23 1 25 0 1
#> 25 6.32 1 34 1 0
#> 177 12.53 1 75 0 0
#> 24 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 61 10.12 1 36 0 1
#> 88 18.37 1 47 0 0
#> 192 16.44 1 31 1 0
#> 15.2 22.68 1 48 0 0
#> 52.1 10.42 1 52 0 1
#> 96.1 14.54 1 33 0 1
#> 79.1 16.23 1 54 1 0
#> 110.1 17.56 1 65 0 1
#> 159 10.55 1 50 0 1
#> 8.1 18.43 1 32 0 0
#> 158 20.14 1 74 1 0
#> 41 18.02 1 40 1 0
#> 130.2 16.47 1 53 0 1
#> 25.1 6.32 1 34 1 0
#> 42 12.43 1 49 0 1
#> 39.2 15.59 1 37 0 1
#> 30.1 17.43 1 78 0 0
#> 25.2 6.32 1 34 1 0
#> 108 18.29 1 39 0 1
#> 184 17.77 1 38 0 0
#> 15.3 22.68 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 140 12.68 1 59 1 0
#> 199 19.81 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 5 16.43 1 51 0 1
#> 39.3 15.59 1 37 0 1
#> 4 17.64 1 NA 0 1
#> 76 19.22 1 54 0 1
#> 158.1 20.14 1 74 1 0
#> 183 9.24 1 67 1 0
#> 69.1 23.23 1 25 0 1
#> 97.2 19.14 1 65 0 1
#> 6.1 15.64 1 39 0 0
#> 150.1 20.33 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 157.1 15.10 1 47 0 0
#> 85 16.44 1 36 0 0
#> 108.1 18.29 1 39 0 1
#> 183.2 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 43 12.10 1 61 0 1
#> 167.2 15.55 1 56 1 0
#> 149 8.37 1 33 1 0
#> 134 17.81 1 47 1 0
#> 114 13.68 1 NA 0 0
#> 166.1 19.98 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 128.2 20.35 1 35 0 1
#> 4.1 17.64 1 NA 0 1
#> 6.2 15.64 1 39 0 0
#> 188 16.16 1 46 0 1
#> 74 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 33 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 165 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 73 24.00 0 NA 0 1
#> 185 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 73.1 24.00 0 NA 0 1
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 112 24.00 0 61 0 0
#> 46 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 135.1 24.00 0 58 1 0
#> 53.1 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 38.1 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 3.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 53.2 24.00 0 32 0 1
#> 71.1 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 196 24.00 0 19 0 0
#> 98 24.00 0 34 1 0
#> 147 24.00 0 76 1 0
#> 2 24.00 0 9 0 0
#> 144 24.00 0 28 0 1
#> 119 24.00 0 17 0 0
#> 160.1 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 11 24.00 0 42 0 1
#> 2.1 24.00 0 9 0 0
#> 144.1 24.00 0 28 0 1
#> 176.1 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 44 24.00 0 56 0 0
#> 162 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 193 24.00 0 45 0 1
#> 115 24.00 0 NA 1 0
#> 38.2 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 160.2 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 152 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 74.1 24.00 0 43 0 1
#> 200.1 24.00 0 64 0 0
#> 65 24.00 0 57 1 0
#> 74.2 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 48 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 75 24.00 0 21 1 0
#> 28.2 24.00 0 67 1 0
#> 73.2 24.00 0 NA 0 1
#> 38.3 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 27.1 24.00 0 63 1 0
#> 44.1 24.00 0 56 0 0
#> 65.1 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 146 24.00 0 63 1 0
#> 94.1 24.00 0 51 0 1
#> 152.1 24.00 0 36 0 1
#> 172.1 24.00 0 41 0 0
#> 74.3 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 62 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.622 NA NA NA
#> 2 age, Cure model 0.0218 NA NA NA
#> 3 grade_ii, Cure model -0.715 NA NA NA
#> 4 grade_iii, Cure model 0.155 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00155 NA NA NA
#> 2 grade_ii, Survival model 1.12 NA NA NA
#> 3 grade_iii, Survival model 0.731 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.62171 0.02177 -0.71484 0.15492
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 247.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.62171195 0.02177092 -0.71484163 0.15491864
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001545186 1.119514717 0.731444209
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.76653987 0.99099654 0.28472145 0.10024454 0.47705159 0.10024454
#> [7] 0.37091992 0.30274312 0.70425236 0.67438827 0.39858427 0.99099654
#> [13] 0.73298239 0.43312236 0.49766551 0.51819694 0.19974844 0.38530815
#> [19] 0.83464002 0.94861690 0.84642565 0.97265002 0.81700545 0.91272983
#> [25] 0.64301903 0.06267403 0.54744079 0.87495313 0.75990768 0.94358182
#> [31] 0.57411180 0.49766551 0.68215451 0.21891864 0.21891864 0.89694481
#> [37] 0.68215451 0.79233620 0.75320284 0.79233620 0.33737707 0.88055195
#> [43] 0.77303728 0.54744079 0.39858427 0.81700545 0.89694481 0.51819694
#> [49] 0.30274312 0.86378841 0.65872756 0.15863044 0.97736302 0.89150984
#> [55] 0.02440953 0.92834836 0.93851672 0.59200479 0.71160136 0.21891864
#> [61] 0.92834836 0.84642565 0.73298239 0.64301903 0.92317909 0.57411180
#> [67] 0.45636902 0.61826490 0.68215451 0.97736302 0.90748318 0.79233620
#> [73] 0.65872756 0.97736302 0.60100961 0.63485583 0.21891864 0.86378841
#> [79] 0.88607080 0.85801969 0.72589010 0.79233620 0.53778128 0.45636902
#> [85] 0.95359247 0.15863044 0.54744079 0.77303728 0.43312236 0.95359247
#> [91] 0.83464002 0.71160136 0.60100961 0.95359247 0.35509890 0.91797354
#> [97] 0.81700545 0.96790703 0.62668629 0.47705159 0.39858427 0.77303728
#> [103] 0.74649220 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 125 127 169 168 166 168.1 153 66 181 171 128 127.1 79
#> 15.65 3.53 22.41 23.72 19.98 23.72 21.33 22.13 16.46 16.57 20.35 3.53 16.23
#> 150 105 170 92 32 157 187 96 77 167 56 110 78
#> 20.33 19.75 19.54 22.92 20.90 15.10 9.92 14.54 7.27 15.55 12.21 17.56 23.88
#> 97 155 26 101 8 105.1 130 15 15.1 37 130.1 39 100
#> 19.14 13.08 15.77 9.97 18.43 19.75 16.47 22.68 22.68 12.52 16.47 15.59 16.07
#> 39.1 175 123 6 97.1 128.1 167.1 37.1 170.1 66.1 60 30 69
#> 15.59 21.91 13.00 15.64 19.14 20.35 15.55 12.52 19.54 22.13 13.15 17.43 23.23
#> 25 177 24 52 61 88 192 15.2 52.1 96.1 79.1 110.1 159
#> 6.32 12.53 23.89 10.42 10.12 18.37 16.44 22.68 10.42 14.54 16.23 17.56 10.55
#> 8.1 158 41 130.2 25.1 42 39.2 30.1 25.2 108 184 15.3 60.1
#> 18.43 20.14 18.02 16.47 6.32 12.43 15.59 17.43 6.32 18.29 17.77 22.68 13.15
#> 140 57 5 39.3 76 158.1 183 69.1 97.2 6.1 150.1 183.1 157.1
#> 12.68 14.46 16.43 15.59 19.22 20.14 9.24 23.23 19.14 15.64 20.33 9.24 15.10
#> 85 108.1 183.2 197 43 167.2 149 134 166.1 128.2 6.2 188 74
#> 16.44 18.29 9.24 21.60 12.10 15.55 8.37 17.81 19.98 20.35 15.64 16.16 24.00
#> 163 174 33 186 135 165 160 104 176 94 185 38 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 17 131 53 112 46 121 135.1 53.1 191 38.1 3 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 141 138 80 109 53.2 71.1 19 196 98 147 2 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 160.1 172 11 2.1 144.1 176.1 27 118 28.1 44 162 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 193 38.2 47 160.2 20 152 1 74.1 200.1 65 74.2 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 11.1 75 28.2 38.3 116 27.1 44.1 65.1 47.1 72 146 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 172.1 74.3 178 62
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[46]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006038278 0.726388343 0.258607477
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.32272349 -0.01179556 0.34381825
#> grade_iii, Cure model
#> 0.94212636
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 26 15.77 1 49 0 1
#> 101 9.97 1 10 0 1
#> 14 12.89 1 21 0 0
#> 140 12.68 1 59 1 0
#> 14.1 12.89 1 21 0 0
#> 59 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 61 10.12 1 36 0 1
#> 58 19.34 1 39 0 0
#> 183 9.24 1 67 1 0
#> 14.2 12.89 1 21 0 0
#> 171 16.57 1 41 0 1
#> 170 19.54 1 43 0 1
#> 93 10.33 1 52 0 1
#> 171.1 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 18 15.21 1 49 1 0
#> 18.1 15.21 1 49 1 0
#> 133 14.65 1 57 0 0
#> 134 17.81 1 47 1 0
#> 39 15.59 1 37 0 1
#> 101.1 9.97 1 10 0 1
#> 183.1 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 86 23.81 1 58 0 1
#> 30 17.43 1 78 0 0
#> 171.2 16.57 1 41 0 1
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 39.1 15.59 1 37 0 1
#> 189.1 10.51 1 NA 1 0
#> 171.3 16.57 1 41 0 1
#> 136 21.83 1 43 0 1
#> 150 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 159 10.55 1 50 0 1
#> 78 23.88 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 175 21.91 1 43 0 0
#> 57 14.46 1 45 0 1
#> 140.1 12.68 1 59 1 0
#> 99 21.19 1 38 0 1
#> 88 18.37 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 166 19.98 1 48 0 0
#> 85 16.44 1 36 0 0
#> 10 10.53 1 34 0 0
#> 100 16.07 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 86.1 23.81 1 58 0 1
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 18.2 15.21 1 49 1 0
#> 96 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 97.2 19.14 1 65 0 1
#> 6 15.64 1 39 0 0
#> 194 22.40 1 38 0 1
#> 164 23.60 1 76 0 1
#> 61.1 10.12 1 36 0 1
#> 140.2 12.68 1 59 1 0
#> 32 20.90 1 37 1 0
#> 106 16.67 1 49 1 0
#> 157 15.10 1 47 0 0
#> 5 16.43 1 51 0 1
#> 139 21.49 1 63 1 0
#> 140.3 12.68 1 59 1 0
#> 86.2 23.81 1 58 0 1
#> 40 18.00 1 28 1 0
#> 93.1 10.33 1 52 0 1
#> 8 18.43 1 32 0 0
#> 50 10.02 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 29.1 15.45 1 68 1 0
#> 37 12.52 1 57 1 0
#> 52 10.42 1 52 0 1
#> 32.1 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 99.1 21.19 1 38 0 1
#> 124.1 9.73 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 100.1 16.07 1 60 0 0
#> 111 17.45 1 47 0 1
#> 113 22.86 1 34 0 0
#> 150.1 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 6.1 15.64 1 39 0 0
#> 127 3.53 1 62 0 1
#> 166.1 19.98 1 48 0 0
#> 128 20.35 1 35 0 1
#> 4 17.64 1 NA 0 1
#> 25 6.32 1 34 1 0
#> 123.2 13.00 1 44 1 0
#> 63 22.77 1 31 1 0
#> 123.3 13.00 1 44 1 0
#> 164.1 23.60 1 76 0 1
#> 107 11.18 1 54 1 0
#> 177 12.53 1 75 0 0
#> 59.1 10.16 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 187 9.92 1 39 1 0
#> 56 12.21 1 60 0 0
#> 10.1 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 79 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 125 15.65 1 67 1 0
#> 76.1 19.22 1 54 0 1
#> 154 12.63 1 20 1 0
#> 52.1 10.42 1 52 0 1
#> 116 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 172 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 11 24.00 0 42 0 1
#> 121 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 152 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 54 24.00 0 53 1 0
#> 156 24.00 0 50 1 0
#> 161 24.00 0 45 0 0
#> 116.2 24.00 0 58 0 1
#> 80 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 116.3 24.00 0 58 0 1
#> 182 24.00 0 35 0 0
#> 135 24.00 0 58 1 0
#> 148 24.00 0 61 1 0
#> 95.1 24.00 0 68 0 1
#> 95.2 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 162 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 146.1 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 33 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 67 24.00 0 25 0 0
#> 143 24.00 0 51 0 0
#> 11.2 24.00 0 42 0 1
#> 142.1 24.00 0 53 0 0
#> 27 24.00 0 63 1 0
#> 80.1 24.00 0 41 0 0
#> 151.1 24.00 0 42 0 0
#> 151.2 24.00 0 42 0 0
#> 72 24.00 0 40 0 1
#> 138 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 146.2 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 126 24.00 0 48 0 0
#> 186 24.00 0 45 1 0
#> 148.2 24.00 0 61 1 0
#> 163 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 80.2 24.00 0 41 0 0
#> 2.1 24.00 0 9 0 0
#> 7 24.00 0 37 1 0
#> 186.1 24.00 0 45 1 0
#> 33.1 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 143.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 178 24.00 0 52 1 0
#> 147 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 143.2 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 161.1 24.00 0 45 0 0
#> 119 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 135.1 24.00 0 58 1 0
#> 193.1 24.00 0 45 0 1
#> 62.1 24.00 0 71 0 0
#> 21.1 24.00 0 47 0 0
#> 44.1 24.00 0 56 0 0
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 135.2 24.00 0 58 1 0
#> 116.4 24.00 0 58 0 1
#> 173 24.00 0 19 0 1
#> 28.1 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.323 NA NA NA
#> 2 age, Cure model -0.0118 NA NA NA
#> 3 grade_ii, Cure model 0.344 NA NA NA
#> 4 grade_iii, Cure model 0.942 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00604 NA NA NA
#> 2 grade_ii, Survival model 0.726 NA NA NA
#> 3 grade_iii, Survival model 0.259 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.3227 -0.0118 0.3438 0.9421
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 253.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.32272349 -0.01179556 0.34381825 0.94212636
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006038278 0.726388343 0.258607477
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.532252768 0.928111929 0.726627923 0.754737448 0.726627923 0.462132078
#> [7] 0.909906462 0.269723296 0.955291825 0.726627923 0.422796558 0.259585440
#> [13] 0.891685663 0.422796558 0.689562111 0.612126069 0.612126069 0.650492469
#> [19] 0.371661099 0.572388877 0.928111929 0.955291825 0.160475415 0.033920132
#> [25] 0.391981280 0.422796558 0.572388877 0.422796558 0.138329867 0.220234625
#> [31] 0.472309749 0.846201711 0.014417407 0.014417407 0.127089426 0.670025269
#> [37] 0.754737448 0.171032769 0.350809549 0.689562111 0.239706538 0.472309749
#> [43] 0.855304588 0.512268283 0.105024952 0.033920132 0.300100567 0.300100567
#> [49] 0.612126069 0.660263284 0.592381154 0.300100567 0.552371632 0.116072291
#> [55] 0.061260952 0.909906462 0.754737448 0.191426624 0.412589471 0.640764208
#> [61] 0.492225492 0.149571759 0.754737448 0.033920132 0.361347492 0.891685663
#> [67] 0.330200874 0.982113220 0.592381154 0.809579981 0.873484914 0.191426624
#> [73] 0.279941774 0.171032769 0.330200874 0.512268283 0.381817819 0.082526398
#> [79] 0.220234625 0.679789111 0.552371632 0.991052199 0.239706538 0.210495603
#> [85] 0.973182689 0.689562111 0.094253178 0.689562111 0.061260952 0.837102984
#> [91] 0.800359357 0.004098096 0.946239453 0.818751977 0.855304588 0.402244707
#> [97] 0.502296096 0.827955308 0.542347613 0.279941774 0.791177260 0.873484914
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 26 101 14 140 14.1 130 61 58 183 14.2 171 170 93
#> 15.77 9.97 12.89 12.68 12.89 16.47 10.12 19.34 9.24 12.89 16.57 19.54 10.33
#> 171.1 123 18 18.1 133 134 39 101.1 183.1 153 86 30 171.2
#> 16.57 13.00 15.21 15.21 14.65 17.81 15.59 9.97 9.24 21.33 23.81 17.43 16.57
#> 39.1 171.3 136 150 192 159 78 78.1 175 57 140.1 99 88
#> 15.59 16.57 21.83 20.33 16.44 10.55 23.88 23.88 21.91 14.46 12.68 21.19 18.37
#> 123.1 166 85 10 100 169 86.1 97 97.1 18.2 96 29 97.2
#> 13.00 19.98 16.44 10.53 16.07 22.41 23.81 19.14 19.14 15.21 14.54 15.45 19.14
#> 6 194 164 61.1 140.2 32 106 157 5 139 140.3 86.2 40
#> 15.64 22.40 23.60 10.12 12.68 20.90 16.67 15.10 16.43 21.49 12.68 23.81 18.00
#> 93.1 8 91 29.1 37 52 32.1 76 99.1 8.1 100.1 111 113
#> 10.33 18.43 5.33 15.45 12.52 10.42 20.90 19.22 21.19 18.43 16.07 17.45 22.86
#> 150.1 13 6.1 127 166.1 128 25 123.2 63 123.3 164.1 107 177
#> 20.33 14.34 15.64 3.53 19.98 20.35 6.32 13.00 22.77 13.00 23.60 11.18 12.53
#> 24 187 56 10.1 23 79 49 125 76.1 154 52.1 116 160
#> 23.89 9.92 12.21 10.53 16.92 16.23 12.19 15.65 19.22 12.63 10.42 24.00 24.00
#> 95 151 74 116.1 172 62 146 84 11 121 11.1 152 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 156 161 116.2 80 142 102 116.3 182 135 148 95.1 95.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 162 131 38 156.1 146.1 64 33 87 67 143 11.2 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 80.1 151.1 151.2 72 138 71 148.1 146.2 20 200 126 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.2 163 53 80.2 2.1 7 186.1 33.1 21 118 143.1 44 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 165 143.2 28 161.1 119 193 191 135.1 193.1 62.1 21.1 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 98 135.2 116.4 173 28.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[47]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008140224 0.148005554 0.274100483
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.23802788 0.01656144 0.91866982
#> grade_iii, Cure model
#> 0.95800268
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 92 22.92 1 47 0 1
#> 133 14.65 1 57 0 0
#> 93 10.33 1 52 0 1
#> 179 18.63 1 42 0 0
#> 42 12.43 1 49 0 1
#> 129 23.41 1 53 1 0
#> 6 15.64 1 39 0 0
#> 149 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 128 20.35 1 35 0 1
#> 134 17.81 1 47 1 0
#> 124 9.73 1 NA 1 0
#> 134.1 17.81 1 47 1 0
#> 107 11.18 1 54 1 0
#> 123 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 128.1 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 166 19.98 1 48 0 0
#> 45 17.42 1 54 0 1
#> 105 19.75 1 60 0 0
#> 128.2 20.35 1 35 0 1
#> 10 10.53 1 34 0 0
#> 63 22.77 1 31 1 0
#> 40 18.00 1 28 1 0
#> 170 19.54 1 43 0 1
#> 130 16.47 1 53 0 1
#> 32 20.90 1 37 1 0
#> 77 7.27 1 67 0 1
#> 32.1 20.90 1 37 1 0
#> 32.2 20.90 1 37 1 0
#> 10.1 10.53 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 128.3 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 110 17.56 1 65 0 1
#> 106 16.67 1 49 1 0
#> 134.2 17.81 1 47 1 0
#> 25 6.32 1 34 1 0
#> 78 23.88 1 43 0 0
#> 29 15.45 1 68 1 0
#> 55 19.34 1 69 0 1
#> 43 12.10 1 61 0 1
#> 77.1 7.27 1 67 0 1
#> 153 21.33 1 55 1 0
#> 175 21.91 1 43 0 0
#> 93.1 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 41 18.02 1 40 1 0
#> 43.1 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 110.1 17.56 1 65 0 1
#> 189 10.51 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 4.1 17.64 1 NA 0 1
#> 32.3 20.90 1 37 1 0
#> 158 20.14 1 74 1 0
#> 97 19.14 1 65 0 1
#> 170.1 19.54 1 43 0 1
#> 155 13.08 1 26 0 0
#> 158.1 20.14 1 74 1 0
#> 177 12.53 1 75 0 0
#> 107.1 11.18 1 54 1 0
#> 189.1 10.51 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 86 23.81 1 58 0 1
#> 76 19.22 1 54 0 1
#> 153.1 21.33 1 55 1 0
#> 107.2 11.18 1 54 1 0
#> 134.3 17.81 1 47 1 0
#> 133.1 14.65 1 57 0 0
#> 43.2 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 42.1 12.43 1 49 0 1
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 10.2 10.53 1 34 0 0
#> 56 12.21 1 60 0 0
#> 106.1 16.67 1 49 1 0
#> 155.1 13.08 1 26 0 0
#> 159 10.55 1 50 0 1
#> 42.2 12.43 1 49 0 1
#> 8 18.43 1 32 0 0
#> 6.1 15.64 1 39 0 0
#> 49 12.19 1 48 1 0
#> 153.2 21.33 1 55 1 0
#> 78.1 23.88 1 43 0 0
#> 168 23.72 1 70 0 0
#> 92.1 22.92 1 47 0 1
#> 29.1 15.45 1 68 1 0
#> 136 21.83 1 43 0 1
#> 192 16.44 1 31 1 0
#> 10.3 10.53 1 34 0 0
#> 111 17.45 1 47 0 1
#> 127 3.53 1 62 0 1
#> 183 9.24 1 67 1 0
#> 70 7.38 1 30 1 0
#> 199.1 19.81 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 77.2 7.27 1 67 0 1
#> 26 15.77 1 49 0 1
#> 66 22.13 1 53 0 0
#> 88 18.37 1 47 0 0
#> 32.4 20.90 1 37 1 0
#> 5 16.43 1 51 0 1
#> 32.5 20.90 1 37 1 0
#> 157 15.10 1 47 0 0
#> 49.1 12.19 1 48 1 0
#> 188 16.16 1 46 0 1
#> 167 15.55 1 56 1 0
#> 158.2 20.14 1 74 1 0
#> 72 24.00 0 40 0 1
#> 118 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 7 24.00 0 37 1 0
#> 104 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 174 24.00 0 49 1 0
#> 151 24.00 0 42 0 0
#> 27 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 186 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 31 24.00 0 36 0 1
#> 200.1 24.00 0 64 0 0
#> 62 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 80 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 2 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 200.2 24.00 0 64 0 0
#> 44 24.00 0 56 0 0
#> 112 24.00 0 61 0 0
#> 131.1 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 83.1 24.00 0 6 0 0
#> 200.3 24.00 0 64 0 0
#> 126 24.00 0 48 0 0
#> 104.1 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 22 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 44.1 24.00 0 56 0 0
#> 178 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 53.1 24.00 0 32 0 1
#> 172 24.00 0 41 0 0
#> 143.1 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 7.1 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 47.1 24.00 0 38 0 1
#> 131.2 24.00 0 66 0 0
#> 131.3 24.00 0 66 0 0
#> 82.1 24.00 0 34 0 0
#> 46 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 34 24.00 0 36 0 0
#> 72.1 24.00 0 40 0 1
#> 74 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 47.2 24.00 0 38 0 1
#> 54 24.00 0 53 1 0
#> 185.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 143.2 24.00 0 51 0 0
#> 143.3 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 67 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 131.4 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 186.1 24.00 0 45 1 0
#> 38 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 72.2 24.00 0 40 0 1
#> 147 24.00 0 76 1 0
#> 109 24.00 0 48 0 0
#> 142.1 24.00 0 53 0 0
#> 198.1 24.00 0 66 0 1
#> 148.1 24.00 0 61 1 0
#> 115 24.00 0 NA 1 0
#> 151.1 24.00 0 42 0 0
#> 65 24.00 0 57 1 0
#> 54.1 24.00 0 53 1 0
#> 84.1 24.00 0 39 0 1
#> 74.1 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.24 NA NA NA
#> 2 age, Cure model 0.0166 NA NA NA
#> 3 grade_ii, Cure model 0.919 NA NA NA
#> 4 grade_iii, Cure model 0.958 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00814 NA NA NA
#> 2 grade_ii, Survival model 0.148 NA NA NA
#> 3 grade_iii, Survival model 0.274 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.23803 0.01656 0.91867 0.95800
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 250.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.23802788 0.01656144 0.91866982 0.95800268
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008140224 0.148005554 0.274100483
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.19507454 0.78552591 0.93270114 0.55461947 0.83090755 0.17342374
#> [7] 0.74536091 0.96130146 0.65177102 0.42219203 0.59703211 0.59703211
#> [13] 0.88603467 0.81156702 0.42219203 0.94992896 0.49094406 0.66677797
#> [19] 0.50052984 0.42219203 0.90957453 0.22934625 0.58866944 0.51000141
#> [25] 0.68883650 0.34693171 0.97258982 0.34693171 0.34693171 0.90957453
#> [31] 0.42219203 0.72459174 0.62857592 0.67423624 0.59703211 0.98903993
#> [37] 0.06034166 0.76568427 0.52818877 0.86809478 0.97258982 0.30919819
#> [43] 0.26307005 0.93270114 0.58025221 0.86809478 0.71046931 0.62857592
#> [49] 0.65177102 0.34693171 0.46248414 0.54597506 0.51000141 0.79857148
#> [55] 0.46248414 0.81805664 0.88603467 0.73850190 0.12208164 0.53715858
#> [61] 0.30919819 0.88603467 0.59703211 0.78552591 0.86809478 0.29455469
#> [67] 0.83090755 0.41090023 0.94419245 0.90957453 0.84956192 0.67423624
#> [73] 0.79857148 0.90368875 0.83090755 0.56320932 0.74536091 0.85579717
#> [79] 0.30919819 0.06034166 0.14942911 0.19507454 0.76568427 0.27919653
#> [85] 0.69609644 0.90957453 0.64406560 0.99453776 0.95563214 0.96695355
#> [91] 0.82450323 0.97258982 0.73157856 0.24651879 0.57176036 0.34693171
#> [97] 0.70331930 0.34693171 0.77891068 0.85579717 0.71756223 0.75892298
#> [103] 0.46248414 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 92 133 93 179 42 129 6 149 30 128 134 134.1 107
#> 22.92 14.65 10.33 18.63 12.43 23.41 15.64 8.37 17.43 20.35 17.81 17.81 11.18
#> 123 128.1 145 166 45 105 128.2 10 63 40 170 130 32
#> 13.00 20.35 10.07 19.98 17.42 19.75 20.35 10.53 22.77 18.00 19.54 16.47 20.90
#> 77 32.1 32.2 10.1 128.3 100 110 106 134.2 25 78 29 55
#> 7.27 20.90 20.90 10.53 20.35 16.07 17.56 16.67 17.81 6.32 23.88 15.45 19.34
#> 43 77.1 153 175 93.1 41 43.1 79 110.1 30.1 32.3 158 97
#> 12.10 7.27 21.33 21.91 10.33 18.02 12.10 16.23 17.56 17.43 20.90 20.14 19.14
#> 170.1 155 158.1 177 107.1 125 86 76 153.1 107.2 134.3 133.1 43.2
#> 19.54 13.08 20.14 12.53 11.18 15.65 23.81 19.22 21.33 11.18 17.81 14.65 12.10
#> 139 42.1 68 61 10.2 56 106.1 155.1 159 42.2 8 6.1 49
#> 21.49 12.43 20.62 10.12 10.53 12.21 16.67 13.08 10.55 12.43 18.43 15.64 12.19
#> 153.2 78.1 168 92.1 29.1 136 192 10.3 111 127 183 70 37
#> 21.33 23.88 23.72 22.92 15.45 21.83 16.44 10.53 17.45 3.53 9.24 7.38 12.52
#> 77.2 26 66 88 32.4 5 32.5 157 49.1 188 167 158.2 72
#> 7.27 15.77 22.13 18.37 20.90 16.43 20.90 15.10 12.19 16.16 15.55 20.14 24.00
#> 118 185 131 198 7 104 152 94 174 151 27 138 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 186 200 31 200.1 62 1 80 102 116 2 122 200.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 112 131.1 53 121 35 83 83.1 200.3 126 104.1 82 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 44.1 178 84 53.1 172 143.1 163 7.1 47 47.1 131.2 131.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 46 132 34 72.1 74 173 47.2 54 185.1 71 17 143.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143.3 31.1 137 67 161 131.4 87 186.1 38 174.1 72.2 147 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 198.1 148.1 151.1 65 54.1 84.1 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[48]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00257875 0.70018122 0.48863265
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.877400176 -0.007565857 -1.041503306
#> grade_iii, Cure model
#> 0.150767321
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 155 13.08 1 26 0 0
#> 42 12.43 1 49 0 1
#> 78 23.88 1 43 0 0
#> 25 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 79 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 8 18.43 1 32 0 0
#> 155.1 13.08 1 26 0 0
#> 76 19.22 1 54 0 1
#> 32 20.90 1 37 1 0
#> 40 18.00 1 28 1 0
#> 41 18.02 1 40 1 0
#> 50 10.02 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 167 15.55 1 56 1 0
#> 190 20.81 1 42 1 0
#> 57 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 181 16.46 1 45 0 1
#> 181.1 16.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 5 16.43 1 51 0 1
#> 190.1 20.81 1 42 1 0
#> 114 13.68 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 40.1 18.00 1 28 1 0
#> 66 22.13 1 53 0 0
#> 170 19.54 1 43 0 1
#> 181.2 16.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 23 16.92 1 61 0 0
#> 79.1 16.23 1 54 1 0
#> 37 12.52 1 57 1 0
#> 171 16.57 1 41 0 1
#> 128 20.35 1 35 0 1
#> 171.1 16.57 1 41 0 1
#> 164 23.60 1 76 0 1
#> 128.1 20.35 1 35 0 1
#> 16 8.71 1 71 0 1
#> 175 21.91 1 43 0 0
#> 68 20.62 1 44 0 0
#> 110.1 17.56 1 65 0 1
#> 39.1 15.59 1 37 0 1
#> 79.2 16.23 1 54 1 0
#> 175.1 21.91 1 43 0 0
#> 40.2 18.00 1 28 1 0
#> 157 15.10 1 47 0 0
#> 40.3 18.00 1 28 1 0
#> 149 8.37 1 33 1 0
#> 113 22.86 1 34 0 0
#> 5.1 16.43 1 51 0 1
#> 139 21.49 1 63 1 0
#> 100 16.07 1 60 0 0
#> 167.1 15.55 1 56 1 0
#> 168 23.72 1 70 0 0
#> 8.1 18.43 1 32 0 0
#> 188 16.16 1 46 0 1
#> 100.1 16.07 1 60 0 0
#> 140 12.68 1 59 1 0
#> 10 10.53 1 34 0 0
#> 91 5.33 1 61 0 1
#> 199 19.81 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 100.2 16.07 1 60 0 0
#> 155.2 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 5.2 16.43 1 51 0 1
#> 130 16.47 1 53 0 1
#> 170.1 19.54 1 43 0 1
#> 58 19.34 1 39 0 0
#> 55 19.34 1 69 0 1
#> 184 17.77 1 38 0 0
#> 15 22.68 1 48 0 0
#> 114.1 13.68 1 NA 0 0
#> 13 14.34 1 54 0 1
#> 113.1 22.86 1 34 0 0
#> 117 17.46 1 26 0 1
#> 26 15.77 1 49 0 1
#> 69 23.23 1 25 0 1
#> 133 14.65 1 57 0 0
#> 16.1 8.71 1 71 0 1
#> 81 14.06 1 34 0 0
#> 55.1 19.34 1 69 0 1
#> 32.1 20.90 1 37 1 0
#> 169 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 99.1 21.19 1 38 0 1
#> 43 12.10 1 61 0 1
#> 89 11.44 1 NA 0 0
#> 55.2 19.34 1 69 0 1
#> 153 21.33 1 55 1 0
#> 96.1 14.54 1 33 0 1
#> 37.1 12.52 1 57 1 0
#> 114.2 13.68 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 8.2 18.43 1 32 0 0
#> 136 21.83 1 43 0 1
#> 8.3 18.43 1 32 0 0
#> 36.1 21.19 1 48 0 1
#> 157.1 15.10 1 47 0 0
#> 8.4 18.43 1 32 0 0
#> 96.2 14.54 1 33 0 1
#> 66.1 22.13 1 53 0 0
#> 16.2 8.71 1 71 0 1
#> 113.2 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 25.1 6.32 1 34 1 0
#> 55.3 19.34 1 69 0 1
#> 130.1 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 116 24.00 0 58 0 1
#> 72 24.00 0 40 0 1
#> 193 24.00 0 45 0 1
#> 165 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 186.1 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 73 24.00 0 NA 0 1
#> 121 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 65 24.00 0 57 1 0
#> 95 24.00 0 68 0 1
#> 35 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#> 200 24.00 0 64 0 0
#> 38 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 11 24.00 0 42 0 1
#> 182 24.00 0 35 0 0
#> 161 24.00 0 45 0 0
#> 121.1 24.00 0 57 1 0
#> 38.1 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 20.1 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 178 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 22.1 24.00 0 52 1 0
#> 148 24.00 0 61 1 0
#> 165.1 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 34 24.00 0 36 0 0
#> 152.1 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 165.2 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 143 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 84 24.00 0 39 0 1
#> 165.3 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 54 24.00 0 53 1 0
#> 191.1 24.00 0 60 0 1
#> 103 24.00 0 56 1 0
#> 103.1 24.00 0 56 1 0
#> 121.2 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 94 24.00 0 51 0 1
#> 31 24.00 0 36 0 1
#> 103.2 24.00 0 56 1 0
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 28.1 24.00 0 67 1 0
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 9.1 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 103.3 24.00 0 56 1 0
#> 174 24.00 0 49 1 0
#> 138.1 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 47.1 24.00 0 38 0 1
#> 126 24.00 0 48 0 0
#> 176 24.00 0 43 0 1
#> 121.3 24.00 0 57 1 0
#> 28.2 24.00 0 67 1 0
#> 54.1 24.00 0 53 1 0
#> 54.2 24.00 0 53 1 0
#> 84.1 24.00 0 39 0 1
#> 80.1 24.00 0 41 0 0
#> 84.2 24.00 0 39 0 1
#> 118.2 24.00 0 44 1 0
#> 28.3 24.00 0 67 1 0
#> 65.1 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 19 24.00 0 57 0 1
#> 74 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.877 NA NA NA
#> 2 age, Cure model -0.00757 NA NA NA
#> 3 grade_ii, Cure model -1.04 NA NA NA
#> 4 grade_iii, Cure model 0.151 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00258 NA NA NA
#> 2 grade_ii, Survival model 0.700 NA NA NA
#> 3 grade_iii, Survival model 0.489 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.877400 -0.007566 -1.041503 0.150767
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 250.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.877400176 -0.007565857 -1.041503306 0.150767321
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00257875 0.70018122 0.48863265
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.817681334 0.862453922 0.914245858 0.007970815 0.979000996 0.802440122
#> [7] 0.694846610 0.756845089 0.455519418 0.862453922 0.436469488 0.286558515
#> [13] 0.510765755 0.501383276 0.928862329 0.772181089 0.308532225 0.840037205
#> [19] 0.553944877 0.638719380 0.638719380 0.597050452 0.671032131 0.308532225
#> [25] 0.241546218 0.510765755 0.141726967 0.370468670 0.638719380 0.446032944
#> [31] 0.588449863 0.694846610 0.899614285 0.605556082 0.339907854 0.605556082
#> [37] 0.043429043 0.339907854 0.950588136 0.170378270 0.329312139 0.553944877
#> [43] 0.756845089 0.694846610 0.170378270 0.510765755 0.787294008 0.510765755
#> [49] 0.971891737 0.074765377 0.671032131 0.214209466 0.725848256 0.772181089
#> [55] 0.024362731 0.455519418 0.718062631 0.725848256 0.892178800 0.936116313
#> [61] 0.992996747 0.360161222 0.725848256 0.862453922 0.241546218 0.671032131
#> [67] 0.622230913 0.370468670 0.390297767 0.390297767 0.545129707 0.112473973
#> [73] 0.847526001 0.074765377 0.571228435 0.749061483 0.060152131 0.810055827
#> [79] 0.950588136 0.854987227 0.390297767 0.286558515 0.127005435 0.884697812
#> [85] 0.241546218 0.921565476 0.390297767 0.228183598 0.817681334 0.899614285
#> [91] 0.662872411 0.455519418 0.199555190 0.455519418 0.241546218 0.787294008
#> [97] 0.455519418 0.817681334 0.141726967 0.950588136 0.074765377 0.579867534
#> [103] 0.979000996 0.390297767 0.622230913 0.943375018 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 96 155 42 78 25 180 79 39 8 155.1 76 32 40
#> 14.54 13.08 12.43 23.88 6.32 14.82 16.23 15.59 18.43 13.08 19.22 20.90 18.00
#> 41 107 167 190 57 110 181 181.1 106 5 190.1 36 40.1
#> 18.02 11.18 15.55 20.81 14.46 17.56 16.46 16.46 16.67 16.43 20.81 21.19 18.00
#> 66 170 181.2 97 23 79.1 37 171 128 171.1 164 128.1 16
#> 22.13 19.54 16.46 19.14 16.92 16.23 12.52 16.57 20.35 16.57 23.60 20.35 8.71
#> 175 68 110.1 39.1 79.2 175.1 40.2 157 40.3 149 113 5.1 139
#> 21.91 20.62 17.56 15.59 16.23 21.91 18.00 15.10 18.00 8.37 22.86 16.43 21.49
#> 100 167.1 168 8.1 188 100.1 140 10 91 150 100.2 155.2 99
#> 16.07 15.55 23.72 18.43 16.16 16.07 12.68 10.53 5.33 20.33 16.07 13.08 21.19
#> 5.2 130 170.1 58 55 184 15 13 113.1 117 26 69 133
#> 16.43 16.47 19.54 19.34 19.34 17.77 22.68 14.34 22.86 17.46 15.77 23.23 14.65
#> 16.1 81 55.1 32.1 169 14 99.1 43 55.2 153 96.1 37.1 85
#> 8.71 14.06 19.34 20.90 22.41 12.89 21.19 12.10 19.34 21.33 14.54 12.52 16.44
#> 8.2 136 8.3 36.1 157.1 8.4 96.2 66.1 16.2 113.2 111 25.1 55.3
#> 18.43 21.83 18.43 21.19 15.10 18.43 14.54 22.13 8.71 22.86 17.45 6.32 19.34
#> 130.1 187 116 72 193 165 186 44 186.1 2 121 20 65
#> 16.47 9.92 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 35 80 193.1 200 38 3 152 11 182 161 121.1 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 20.1 22 178 109 22.1 148 165.1 198 34 152.1 138 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.2 172 196 143 151 84 165.3 191 54 191.1 103 103.1 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 118.1 120.1 1 94 31 103.2 48 9 1.1 28.1 137 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 47 103.3 174 138.1 160 95.1 47.1 126 176 121.3 28.2 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.2 84.1 80.1 84.2 118.2 28.3 65.1 67 19 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[49]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008739633 0.647480821 0.053201911
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.81662637 0.01117173 0.29565540
#> grade_iii, Cure model
#> 1.43943550
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 179 18.63 1 42 0 0
#> 154 12.63 1 20 1 0
#> 101 9.97 1 10 0 1
#> 88 18.37 1 47 0 0
#> 86 23.81 1 58 0 1
#> 43 12.10 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 107 11.18 1 54 1 0
#> 18 15.21 1 49 1 0
#> 66 22.13 1 53 0 0
#> 45 17.42 1 54 0 1
#> 43.1 12.10 1 61 0 1
#> 181 16.46 1 45 0 1
#> 107.1 11.18 1 54 1 0
#> 124.1 9.73 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 15 22.68 1 48 0 0
#> 18.1 15.21 1 49 1 0
#> 40 18.00 1 28 1 0
#> 125 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 145 10.07 1 65 1 0
#> 114 13.68 1 NA 0 0
#> 40.1 18.00 1 28 1 0
#> 129 23.41 1 53 1 0
#> 40.2 18.00 1 28 1 0
#> 128 20.35 1 35 0 1
#> 90 20.94 1 50 0 1
#> 14 12.89 1 21 0 0
#> 117.1 17.46 1 26 0 1
#> 77 7.27 1 67 0 1
#> 6 15.64 1 39 0 0
#> 45.1 17.42 1 54 0 1
#> 69 23.23 1 25 0 1
#> 92 22.92 1 47 0 1
#> 108 18.29 1 39 0 1
#> 114.1 13.68 1 NA 0 0
#> 117.2 17.46 1 26 0 1
#> 125.1 15.65 1 67 1 0
#> 167 15.55 1 56 1 0
#> 8 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 113 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 15.1 22.68 1 48 0 0
#> 128.1 20.35 1 35 0 1
#> 6.1 15.64 1 39 0 0
#> 36 21.19 1 48 0 1
#> 158 20.14 1 74 1 0
#> 159 10.55 1 50 0 1
#> 58 19.34 1 39 0 0
#> 136 21.83 1 43 0 1
#> 184 17.77 1 38 0 0
#> 99 21.19 1 38 0 1
#> 51 18.23 1 83 0 1
#> 108.1 18.29 1 39 0 1
#> 63.1 22.77 1 31 1 0
#> 166 19.98 1 48 0 0
#> 97.1 19.14 1 65 0 1
#> 91 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 149 8.37 1 33 1 0
#> 107.2 11.18 1 54 1 0
#> 86.1 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 68 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 37 12.52 1 57 1 0
#> 145.1 10.07 1 65 1 0
#> 26 15.77 1 49 0 1
#> 99.1 21.19 1 38 0 1
#> 88.1 18.37 1 47 0 0
#> 40.3 18.00 1 28 1 0
#> 99.2 21.19 1 38 0 1
#> 190 20.81 1 42 1 0
#> 110 17.56 1 65 0 1
#> 63.2 22.77 1 31 1 0
#> 91.1 5.33 1 61 0 1
#> 55 19.34 1 69 0 1
#> 24 23.89 1 38 0 0
#> 175 21.91 1 43 0 0
#> 70 7.38 1 30 1 0
#> 79 16.23 1 54 1 0
#> 107.3 11.18 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 79.1 16.23 1 54 1 0
#> 60 13.15 1 38 1 0
#> 56 12.21 1 60 0 0
#> 90.1 20.94 1 50 0 1
#> 128.2 20.35 1 35 0 1
#> 97.2 19.14 1 65 0 1
#> 86.2 23.81 1 58 0 1
#> 97.3 19.14 1 65 0 1
#> 134 17.81 1 47 1 0
#> 107.4 11.18 1 54 1 0
#> 70.1 7.38 1 30 1 0
#> 29 15.45 1 68 1 0
#> 99.3 21.19 1 38 0 1
#> 130 16.47 1 53 0 1
#> 60.1 13.15 1 38 1 0
#> 107.5 11.18 1 54 1 0
#> 55.1 19.34 1 69 0 1
#> 4 17.64 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 179.1 18.63 1 42 0 0
#> 26.1 15.77 1 49 0 1
#> 97.4 19.14 1 65 0 1
#> 182 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 104 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 120 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 53 24.00 0 32 0 1
#> 146 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 186 24.00 0 45 1 0
#> 137 24.00 0 45 1 0
#> 115.1 24.00 0 NA 1 0
#> 143 24.00 0 51 0 0
#> 115.2 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 144 24.00 0 28 0 1
#> 11 24.00 0 42 0 1
#> 7 24.00 0 37 1 0
#> 54 24.00 0 53 1 0
#> 94 24.00 0 51 0 1
#> 31.1 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 196 24.00 0 19 0 0
#> 82 24.00 0 34 0 0
#> 162 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 115.3 24.00 0 NA 1 0
#> 126 24.00 0 48 0 0
#> 80 24.00 0 41 0 0
#> 174 24.00 0 49 1 0
#> 148.1 24.00 0 61 1 0
#> 173.1 24.00 0 19 0 1
#> 34 24.00 0 36 0 0
#> 31.2 24.00 0 36 0 1
#> 54.1 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 87 24.00 0 27 0 0
#> 3 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 73 24.00 0 NA 0 1
#> 126.1 24.00 0 48 0 0
#> 182.1 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 87.1 24.00 0 27 0 0
#> 148.2 24.00 0 61 1 0
#> 87.2 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 103.1 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 48 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 112 24.00 0 61 0 0
#> 126.2 24.00 0 48 0 0
#> 48.1 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 163.1 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 1.1 24.00 0 23 1 0
#> 160.2 24.00 0 31 1 0
#> 143.1 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 182.2 24.00 0 35 0 0
#> 198.1 24.00 0 66 0 1
#> 142.1 24.00 0 53 0 0
#> 73.1 24.00 0 NA 0 1
#> 135 24.00 0 58 1 0
#> 160.3 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 22 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 138 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 12.1 24.00 0 63 0 0
#> 135.1 24.00 0 58 1 0
#> 33 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 2.1 24.00 0 9 0 0
#> 27 24.00 0 63 1 0
#> 148.3 24.00 0 61 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.817 NA NA NA
#> 2 age, Cure model 0.0112 NA NA NA
#> 3 grade_ii, Cure model 0.296 NA NA NA
#> 4 grade_iii, Cure model 1.44 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00874 NA NA NA
#> 2 grade_ii, Survival model 0.647 NA NA NA
#> 3 grade_iii, Survival model 0.0532 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.81663 0.01117 0.29566 1.43944
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 256.4
#> Residual Deviance: 239.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.81662637 0.01117173 0.29565540 1.43943550
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008739633 0.647480821 0.053201911
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8623780 0.5915990 0.8794555 0.9666531 0.6164439 0.1194595 0.8960531
#> [8] 0.2650209 0.7077356 0.9068978 0.8274330 0.3307467 0.7288938 0.8960531
#> [15] 0.7567972 0.9068978 0.9519307 0.3048092 0.8274330 0.6567239 0.7900554
#> [22] 0.7428806 0.9569270 0.6567239 0.1876064 0.6567239 0.4657303 0.4229241
#> [29] 0.8681026 0.7077356 0.9858638 0.8026565 0.7288938 0.2080174 0.2278236
#> [36] 0.6327021 0.7077356 0.7900554 0.8151777 0.6081487 0.5505909 0.2466643
#> [43] 0.8738196 0.3048092 0.4657303 0.8026565 0.3688589 0.4955470 0.9368539
#> [50] 0.5238666 0.3563863 0.6932823 0.3688589 0.6487610 0.6327021 0.2650209
#> [57] 0.5051705 0.5505909 0.9906073 0.9469228 0.9715247 0.9068978 0.1194595
#> [64] 0.8450816 0.4552761 0.9418973 0.8850456 0.9569270 0.7769459 0.3688589
#> [71] 0.6164439 0.6567239 0.3688589 0.4447081 0.7005410 0.2650209 0.9906073
#> [78] 0.5238666 0.0582979 0.3436755 0.9763588 0.7636981 0.9068978 0.5051705
#> [85] 0.7636981 0.8509476 0.8905611 0.4229241 0.4657303 0.5505909 0.1194595
#> [92] 0.5505909 0.6859935 0.9068978 0.9763588 0.8213616 0.3688589 0.7498607
#> [99] 0.8509476 0.9068978 0.5238666 0.8391989 0.5915990 0.7769459 0.5505909
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 155 179 154 101 88 86 43 63 117 107 18 66 45
#> 13.08 18.63 12.63 9.97 18.37 23.81 12.10 22.77 17.46 11.18 15.21 22.13 17.42
#> 43.1 181 107.1 61 15 18.1 40 125 23 145 40.1 129 40.2
#> 12.10 16.46 11.18 10.12 22.68 15.21 18.00 15.65 16.92 10.07 18.00 23.41 18.00
#> 128 90 14 117.1 77 6 45.1 69 92 108 117.2 125.1 167
#> 20.35 20.94 12.89 17.46 7.27 15.64 17.42 23.23 22.92 18.29 17.46 15.65 15.55
#> 8 97 113 140 15.1 128.1 6.1 36 158 159 58 136 184
#> 18.43 19.14 22.86 12.68 22.68 20.35 15.64 21.19 20.14 10.55 19.34 21.83 17.77
#> 99 51 108.1 63.1 166 97.1 91 93 149 107.2 86.1 96 68
#> 21.19 18.23 18.29 22.77 19.98 19.14 5.33 10.33 8.37 11.18 23.81 14.54 20.62
#> 52 37 145.1 26 99.1 88.1 40.3 99.2 190 110 63.2 91.1 55
#> 10.42 12.52 10.07 15.77 21.19 18.37 18.00 21.19 20.81 17.56 22.77 5.33 19.34
#> 24 175 70 79 107.3 166.1 79.1 60 56 90.1 128.2 97.2 86.2
#> 23.89 21.91 7.38 16.23 11.18 19.98 16.23 13.15 12.21 20.94 20.35 19.14 23.81
#> 97.3 134 107.4 70.1 29 99.3 130 60.1 107.5 55.1 157 179.1 26.1
#> 19.14 17.81 11.18 7.38 15.45 21.19 16.47 13.15 11.18 19.34 15.10 18.63 15.77
#> 97.4 182 173 141 31 104 121 120 148 53 146 47 163
#> 19.14 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 186 137 143 103 144 11 7 54 94 31.1 160 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 82 162 142 126 80 174 148.1 173.1 34 31.2 54.1 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 3 1 126.1 182.1 46 87.1 148.2 87.2 156 103.1 9 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 7.1 112 126.2 48.1 160.1 174.1 163.1 21 35 1.1 160.2 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 182.2 198.1 142.1 135 160.3 2 22 84 138 47.1 12.1 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 67 2.1 27 148.3
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[50]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002905154 0.788232186 0.268003416
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.173824138 0.008351813 -0.398818485
#> grade_iii, Cure model
#> 0.331679195
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 90 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 153 21.33 1 55 1 0
#> 189 10.51 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 105 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 190 20.81 1 42 1 0
#> 36.1 21.19 1 48 0 1
#> 78 23.88 1 43 0 0
#> 128 20.35 1 35 0 1
#> 90.1 20.94 1 50 0 1
#> 60 13.15 1 38 1 0
#> 105.1 19.75 1 60 0 0
#> 188 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 105.2 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 127 3.53 1 62 0 1
#> 52 10.42 1 52 0 1
#> 130 16.47 1 53 0 1
#> 85 16.44 1 36 0 0
#> 177 12.53 1 75 0 0
#> 78.1 23.88 1 43 0 0
#> 69 23.23 1 25 0 1
#> 56 12.21 1 60 0 0
#> 130.1 16.47 1 53 0 1
#> 78.2 23.88 1 43 0 0
#> 37 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 114 13.68 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 166 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 177.1 12.53 1 75 0 0
#> 123 13.00 1 44 1 0
#> 101 9.97 1 10 0 1
#> 58 19.34 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 14 12.89 1 21 0 0
#> 167.1 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 41.1 18.02 1 40 1 0
#> 164 23.60 1 76 0 1
#> 177.2 12.53 1 75 0 0
#> 91 5.33 1 61 0 1
#> 40.1 18.00 1 28 1 0
#> 15 22.68 1 48 0 0
#> 15.1 22.68 1 48 0 0
#> 169 22.41 1 46 0 0
#> 59 10.16 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 170 19.54 1 43 0 1
#> 175 21.91 1 43 0 0
#> 79.1 16.23 1 54 1 0
#> 128.1 20.35 1 35 0 1
#> 97 19.14 1 65 0 1
#> 190.1 20.81 1 42 1 0
#> 49 12.19 1 48 1 0
#> 194 22.40 1 38 0 1
#> 79.2 16.23 1 54 1 0
#> 58.1 19.34 1 39 0 0
#> 16 8.71 1 71 0 1
#> 6 15.64 1 39 0 0
#> 164.1 23.60 1 76 0 1
#> 25 6.32 1 34 1 0
#> 106 16.67 1 49 1 0
#> 6.1 15.64 1 39 0 0
#> 195 11.76 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 168 23.72 1 70 0 0
#> 8.1 18.43 1 32 0 0
#> 23 16.92 1 61 0 0
#> 194.1 22.40 1 38 0 1
#> 36.2 21.19 1 48 0 1
#> 16.1 8.71 1 71 0 1
#> 88 18.37 1 47 0 0
#> 166.1 19.98 1 48 0 0
#> 170.1 19.54 1 43 0 1
#> 91.1 5.33 1 61 0 1
#> 145 10.07 1 65 1 0
#> 49.1 12.19 1 48 1 0
#> 70 7.38 1 30 1 0
#> 59.1 10.16 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 96 14.54 1 33 0 1
#> 93.1 10.33 1 52 0 1
#> 149 8.37 1 33 1 0
#> 36.3 21.19 1 48 0 1
#> 8.2 18.43 1 32 0 0
#> 187 9.92 1 39 1 0
#> 76 19.22 1 54 0 1
#> 61 10.12 1 36 0 1
#> 59.2 10.16 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 155 13.08 1 26 0 0
#> 158 20.14 1 74 1 0
#> 76.1 19.22 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 124.1 9.73 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 40.2 18.00 1 28 1 0
#> 155.1 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 57 14.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 129 23.41 1 53 1 0
#> 199.1 19.81 1 NA 0 1
#> 186 24.00 0 45 1 0
#> 178 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 94 24.00 0 51 0 1
#> 28 24.00 0 67 1 0
#> 22 24.00 0 52 1 0
#> 147 24.00 0 76 1 0
#> 104 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 83 24.00 0 6 0 0
#> 65 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 138 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 83.1 24.00 0 6 0 0
#> 185 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 82 24.00 0 34 0 0
#> 98 24.00 0 34 1 0
#> 84 24.00 0 39 0 1
#> 165 24.00 0 47 0 0
#> 22.1 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 73 24.00 0 NA 0 1
#> 17 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 21 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 122.1 24.00 0 66 0 0
#> 160.1 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 178.2 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 103 24.00 0 56 1 0
#> 73.1 24.00 0 NA 0 1
#> 98.1 24.00 0 34 1 0
#> 104.1 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 62 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 62.1 24.00 0 71 0 0
#> 104.2 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 147.1 24.00 0 76 1 0
#> 122.2 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 147.2 24.00 0 76 1 0
#> 191.1 24.00 0 60 0 1
#> 94.1 24.00 0 51 0 1
#> 3 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 185.1 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 1 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 104.3 24.00 0 50 1 0
#> 162.1 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 72.2 24.00 0 40 0 1
#> 176.1 24.00 0 43 0 1
#> 72.3 24.00 0 40 0 1
#> 160.2 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 19.1 24.00 0 57 0 1
#> 80 24.00 0 41 0 0
#> 103.1 24.00 0 56 1 0
#> 19.2 24.00 0 57 0 1
#> 20 24.00 0 46 1 0
#> 20.1 24.00 0 46 1 0
#> 73.2 24.00 0 NA 0 1
#> 94.2 24.00 0 51 0 1
#> 176.2 24.00 0 43 0 1
#> 138.2 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 11 24.00 0 42 0 1
#> 71 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 115 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.174 NA NA NA
#> 2 age, Cure model 0.00835 NA NA NA
#> 3 grade_ii, Cure model -0.399 NA NA NA
#> 4 grade_iii, Cure model 0.332 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00291 NA NA NA
#> 2 grade_ii, Survival model 0.788 NA NA NA
#> 3 grade_iii, Survival model 0.268 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.173824 0.008352 -0.398818 0.331679
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 253.7
#> Residual Deviance: 248.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.173824138 0.008351813 -0.398818485 0.331679195
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002905154 0.788232186 0.268003416
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.72242995 0.26895510 0.22429465 0.21182304 0.04922549 0.37519104
#> [7] 0.55813243 0.30337142 0.22429465 0.01585289 0.32417188 0.26895510
#> [13] 0.76546996 0.37519104 0.67815205 0.65157766 0.80762647 0.37519104
#> [19] 0.53834263 0.99229360 0.88163082 0.62377777 0.64225713 0.81595811
#> [25] 0.01585289 0.12136940 0.85724080 0.62377777 0.01585289 0.84084645
#> [31] 0.70496291 0.73113169 0.35493426 0.81595811 0.79082049 0.92189125
#> [37] 0.42589498 0.88972915 0.79922086 0.70496291 0.52798695 0.53834263
#> [43] 0.07998290 0.81595811 0.97692974 0.55813243 0.13445517 0.13445517
#> [49] 0.15998055 0.48723626 0.40555137 0.19867473 0.65157766 0.32417188
#> [55] 0.46668243 0.30337142 0.86549023 0.17343821 0.65157766 0.42589498
#> [61] 0.93780541 0.68711142 0.07998290 0.96920577 0.61443496 0.68711142
#> [67] 0.47694663 0.06425845 0.48723626 0.60496141 0.17343821 0.22429465
#> [73] 0.93780541 0.51762575 0.35493426 0.40555137 0.97692974 0.91388263
#> [79] 0.86549023 0.96142022 0.84084645 0.73974043 0.88972915 0.95357009
#> [85] 0.22429465 0.48723626 0.92988115 0.44634337 0.90581596 0.58604126
#> [91] 0.77394213 0.34473412 0.44634337 0.59551189 0.55813243 0.77394213
#> [97] 0.29203810 0.74833039 0.75690588 0.10797375 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 29 90 36 153 86 105 40 190 36.1 78 128 90.1 60
#> 15.45 20.94 21.19 21.33 23.81 19.75 18.00 20.81 21.19 23.88 20.35 20.94 13.15
#> 105.1 188 79 140 105.2 41 127 52 130 85 177 78.1 69
#> 19.75 16.16 16.23 12.68 19.75 18.02 3.53 10.42 16.47 16.44 12.53 23.88 23.23
#> 56 130.1 78.2 37 167 18 166 177.1 123 101 58 93 14
#> 12.21 16.47 23.88 12.52 15.55 15.21 19.98 12.53 13.00 9.97 19.34 10.33 12.89
#> 167.1 51 41.1 164 177.2 91 40.1 15 15.1 169 8 170 175
#> 15.55 18.23 18.02 23.60 12.53 5.33 18.00 22.68 22.68 22.41 18.43 19.54 21.91
#> 79.1 128.1 97 190.1 49 194 79.2 58.1 16 6 164.1 25 106
#> 16.23 20.35 19.14 20.81 12.19 22.40 16.23 19.34 8.71 15.64 23.60 6.32 16.67
#> 6.1 179 168 8.1 23 194.1 36.2 16.1 88 166.1 170.1 91.1 145
#> 15.64 18.63 23.72 18.43 16.92 22.40 21.19 8.71 18.37 19.98 19.54 5.33 10.07
#> 49.1 70 37.1 96 93.1 149 36.3 8.2 187 76 61 184 155
#> 12.19 7.38 12.52 14.54 10.33 8.37 21.19 18.43 9.92 19.22 10.12 17.77 13.08
#> 158 76.1 111 40.2 155.1 32 57 13 129 186 178 87 94
#> 20.14 19.22 17.45 18.00 13.08 20.90 14.46 14.34 23.41 24.00 24.00 24.00 24.00
#> 28 22 147 104 34 83 65 148 138 160 191 83.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 82 98 84 165 22.1 72 17 135 21 122 178.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 160.1 54 178.2 38 138.1 182 103 98.1 104.1 173 62 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 104.2 176 196 147.1 122.2 46 109 147.2 191.1 94.1 3 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 7 1 120 162 72.1 19 104.3 162.1 165.1 72.2 176.1 72.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.2 200 19.1 80 103.1 19.2 20 20.1 94.2 176.2 138.2 1.1 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 200.1
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[51]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001203719 0.263225593 0.169535778
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.635349695 0.007104776 0.285745462
#> grade_iii, Cure model
#> 1.168478324
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 55 19.34 1 69 0 1
#> 85 16.44 1 36 0 0
#> 26 15.77 1 49 0 1
#> 181 16.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 69 23.23 1 25 0 1
#> 111 17.45 1 47 0 1
#> 88 18.37 1 47 0 0
#> 175 21.91 1 43 0 0
#> 101 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 124 9.73 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 169 22.41 1 46 0 0
#> 154 12.63 1 20 1 0
#> 153 21.33 1 55 1 0
#> 58 19.34 1 39 0 0
#> 183.1 9.24 1 67 1 0
#> 130 16.47 1 53 0 1
#> 150 20.33 1 48 0 0
#> 128 20.35 1 35 0 1
#> 170 19.54 1 43 0 1
#> 14 12.89 1 21 0 0
#> 6 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 170.1 19.54 1 43 0 1
#> 43 12.10 1 61 0 1
#> 180 14.82 1 37 0 0
#> 106 16.67 1 49 1 0
#> 180.1 14.82 1 37 0 0
#> 89 11.44 1 NA 0 0
#> 106.1 16.67 1 49 1 0
#> 153.1 21.33 1 55 1 0
#> 60 13.15 1 38 1 0
#> 88.1 18.37 1 47 0 0
#> 159 10.55 1 50 0 1
#> 23 16.92 1 61 0 0
#> 190 20.81 1 42 1 0
#> 70 7.38 1 30 1 0
#> 107 11.18 1 54 1 0
#> 60.1 13.15 1 38 1 0
#> 175.1 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 187 9.92 1 39 1 0
#> 56 12.21 1 60 0 0
#> 159.1 10.55 1 50 0 1
#> 125 15.65 1 67 1 0
#> 167 15.55 1 56 1 0
#> 107.1 11.18 1 54 1 0
#> 139 21.49 1 63 1 0
#> 26.1 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 66 22.13 1 53 0 0
#> 113 22.86 1 34 0 0
#> 70.1 7.38 1 30 1 0
#> 30 17.43 1 78 0 0
#> 55.1 19.34 1 69 0 1
#> 108.1 18.29 1 39 0 1
#> 90 20.94 1 50 0 1
#> 133 14.65 1 57 0 0
#> 55.2 19.34 1 69 0 1
#> 192 16.44 1 31 1 0
#> 45 17.42 1 54 0 1
#> 123 13.00 1 44 1 0
#> 123.1 13.00 1 44 1 0
#> 86 23.81 1 58 0 1
#> 133.1 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 130.1 16.47 1 53 0 1
#> 96 14.54 1 33 0 1
#> 81 14.06 1 34 0 0
#> 100 16.07 1 60 0 0
#> 36 21.19 1 48 0 1
#> 183.2 9.24 1 67 1 0
#> 41 18.02 1 40 1 0
#> 41.1 18.02 1 40 1 0
#> 114 13.68 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 40 18.00 1 28 1 0
#> 42 12.43 1 49 0 1
#> 58.1 19.34 1 39 0 0
#> 39 15.59 1 37 0 1
#> 63 22.77 1 31 1 0
#> 199.1 19.81 1 NA 0 1
#> 50 10.02 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 139.1 21.49 1 63 1 0
#> 114.1 13.68 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 23.1 16.92 1 61 0 0
#> 167.2 15.55 1 56 1 0
#> 149 8.37 1 33 1 0
#> 129 23.41 1 53 1 0
#> 145 10.07 1 65 1 0
#> 45.1 17.42 1 54 0 1
#> 188 16.16 1 46 0 1
#> 77 7.27 1 67 0 1
#> 39.1 15.59 1 37 0 1
#> 89.1 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 158 20.14 1 74 1 0
#> 181.1 16.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 159.2 10.55 1 50 0 1
#> 99 21.19 1 38 0 1
#> 63.1 22.77 1 31 1 0
#> 128.1 20.35 1 35 0 1
#> 178 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 163 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 147.1 24.00 0 76 1 0
#> 104 24.00 0 50 1 0
#> 65.1 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 34 24.00 0 36 0 0
#> 19 24.00 0 57 0 1
#> 95 24.00 0 68 0 1
#> 31 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 82 24.00 0 34 0 0
#> 143 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 118 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 2 24.00 0 9 0 0
#> 12.1 24.00 0 63 0 0
#> 119 24.00 0 17 0 0
#> 126 24.00 0 48 0 0
#> 156.1 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 3 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 65.2 24.00 0 57 1 0
#> 160 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 116.1 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 185.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 33 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 104.1 24.00 0 50 1 0
#> 3.1 24.00 0 31 1 0
#> 185.2 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 44.1 24.00 0 56 0 0
#> 53 24.00 0 32 0 1
#> 173 24.00 0 19 0 1
#> 27 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 17 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 67 24.00 0 25 0 0
#> 87 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 67.1 24.00 0 25 0 0
#> 160.1 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 147.2 24.00 0 76 1 0
#> 148 24.00 0 61 1 0
#> 173.1 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 119.1 24.00 0 17 0 0
#> 173.2 24.00 0 19 0 1
#> 109 24.00 0 48 0 0
#> 147.3 24.00 0 76 1 0
#> 84 24.00 0 39 0 1
#> 27.1 24.00 0 63 1 0
#> 44.2 24.00 0 56 0 0
#> 137 24.00 0 45 1 0
#> 146 24.00 0 63 1 0
#> 53.1 24.00 0 32 0 1
#> 135 24.00 0 58 1 0
#> 160.2 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 147.4 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 71.1 24.00 0 51 0 0
#> 67.2 24.00 0 25 0 0
#> 118.1 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.635 NA NA NA
#> 2 age, Cure model 0.00710 NA NA NA
#> 3 grade_ii, Cure model 0.286 NA NA NA
#> 4 grade_iii, Cure model 1.17 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00120 NA NA NA
#> 2 grade_ii, Survival model 0.263 NA NA NA
#> 3 grade_iii, Survival model 0.170 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.635350 0.007105 0.285745 1.168478
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 249.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.635349695 0.007104776 0.285745462 1.168478324
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001203719 0.263225593 0.169535778
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.37312098 0.60695576 0.65110124 0.58904397 0.17618335 0.05365716
#> [7] 0.49703830 0.43011170 0.15089782 0.92049611 0.93667948 0.44948883
#> [13] 0.12413192 0.83863117 0.22479841 0.37312098 0.93667948 0.57099463
#> [19] 0.32171130 0.30097038 0.35298314 0.83028501 0.67738114 0.11062499
#> [25] 0.35298314 0.86353912 0.72888350 0.55279416 0.72888350 0.55279416
#> [31] 0.22479841 0.79693257 0.43011170 0.88815029 0.53436307 0.29023767
#> [37] 0.96842617 0.87180895 0.79693257 0.15089782 0.99211268 0.92860061
#> [43] 0.85524746 0.88815029 0.66861406 0.70344934 0.87180895 0.20161922
#> [49] 0.65110124 0.34261792 0.70344934 0.13755721 0.06944021 0.96842617
#> [55] 0.50646952 0.37312098 0.44948883 0.26888368 0.74592163 0.37312098
#> [61] 0.60695576 0.51588348 0.81367233 0.81367233 0.01676258 0.74592163
#> [67] 0.42028550 0.26888368 0.57099463 0.76293219 0.78845346 0.64222344
#> [73] 0.24708375 0.93667948 0.46866630 0.46866630 0.60695576 0.48756147
#> [79] 0.84694978 0.37312098 0.68614277 0.08509079 0.20161922 0.18907802
#> [85] 0.53436307 0.70344934 0.96045735 0.03682906 0.91237737 0.51588348
#> [91] 0.63333644 0.98420797 0.68614277 0.77146315 0.33223404 0.58904397
#> [97] 0.77997053 0.88815029 0.24708375 0.08509079 0.30097038 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 55 85 26 181 136 69 111 88 175 101 183 108 169
#> 19.34 16.44 15.77 16.46 21.83 23.23 17.45 18.37 21.91 9.97 9.24 18.29 22.41
#> 154 153 58 183.1 130 150 128 170 14 6 15 170.1 43
#> 12.63 21.33 19.34 9.24 16.47 20.33 20.35 19.54 12.89 15.64 22.68 19.54 12.10
#> 180 106 180.1 106.1 153.1 60 88.1 159 23 190 70 107 60.1
#> 14.82 16.67 14.82 16.67 21.33 13.15 18.37 10.55 16.92 20.81 7.38 11.18 13.15
#> 175.1 127 187 56 159.1 125 167 107.1 139 26.1 166 167.1 66
#> 21.91 3.53 9.92 12.21 10.55 15.65 15.55 11.18 21.49 15.77 19.98 15.55 22.13
#> 113 70.1 30 55.1 108.1 90 133 55.2 192 45 123 123.1 86
#> 22.86 7.38 17.43 19.34 18.29 20.94 14.65 19.34 16.44 17.42 13.00 13.00 23.81
#> 133.1 76 90.1 130.1 96 81 100 36 183.2 41 41.1 192.1 40
#> 14.65 19.22 20.94 16.47 14.54 14.06 16.07 21.19 9.24 18.02 18.02 16.44 18.00
#> 42 58.1 39 63 139.1 197 23.1 167.2 149 129 145 45.1 188
#> 12.43 19.34 15.59 22.77 21.49 21.60 16.92 15.55 8.37 23.41 10.07 17.42 16.16
#> 77 39.1 57 158 181.1 13 159.2 99 63.1 128.1 178 156 131
#> 7.27 15.59 14.46 20.14 16.46 14.34 10.55 21.19 22.77 20.35 24.00 24.00 24.00
#> 147 163 65 147.1 104 65.1 80 185 62 193 34 19 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 151 82 143 143.1 44 118 116 12 72 2 12.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 156.1 7 3 71 21 65.2 160 182 116.1 174 185.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 20 104.1 3.1 185.2 38 72.1 165 22 94 44.1 53 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 186 17 64 67 87 67.1 160.1 1 147.2 148 173.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 173.2 109 147.3 84 27.1 44.2 137 146 53.1 135 160.2 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.4 102 71.1 67.2 118.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[52]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001483094 0.306144029 0.037095854
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.745248488 0.009278938 0.696028708
#> grade_iii, Cure model
#> 0.835785995
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 45 17.42 1 54 0 1
#> 25 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 50 10.02 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 56 12.21 1 60 0 0
#> 52 10.42 1 52 0 1
#> 110 17.56 1 65 0 1
#> 187 9.92 1 39 1 0
#> 127 3.53 1 62 0 1
#> 155 13.08 1 26 0 0
#> 125 15.65 1 67 1 0
#> 158 20.14 1 74 1 0
#> 117 17.46 1 26 0 1
#> 32 20.90 1 37 1 0
#> 79 16.23 1 54 1 0
#> 66 22.13 1 53 0 0
#> 69 23.23 1 25 0 1
#> 49 12.19 1 48 1 0
#> 90 20.94 1 50 0 1
#> 69.1 23.23 1 25 0 1
#> 5 16.43 1 51 0 1
#> 92 22.92 1 47 0 1
#> 70 7.38 1 30 1 0
#> 13 14.34 1 54 0 1
#> 30 17.43 1 78 0 0
#> 93 10.33 1 52 0 1
#> 169 22.41 1 46 0 0
#> 168 23.72 1 70 0 0
#> 77 7.27 1 67 0 1
#> 6 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 117.1 17.46 1 26 0 1
#> 189 10.51 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 10 10.53 1 34 0 0
#> 69.2 23.23 1 25 0 1
#> 167 15.55 1 56 1 0
#> 81 14.06 1 34 0 0
#> 25.1 6.32 1 34 1 0
#> 190 20.81 1 42 1 0
#> 101 9.97 1 10 0 1
#> 167.1 15.55 1 56 1 0
#> 192 16.44 1 31 1 0
#> 133 14.65 1 57 0 0
#> 23 16.92 1 61 0 0
#> 92.1 22.92 1 47 0 1
#> 197.1 21.60 1 69 1 0
#> 170.1 19.54 1 43 0 1
#> 128 20.35 1 35 0 1
#> 40 18.00 1 28 1 0
#> 133.1 14.65 1 57 0 0
#> 111 17.45 1 47 0 1
#> 134 17.81 1 47 1 0
#> 97 19.14 1 65 0 1
#> 183 9.24 1 67 1 0
#> 113 22.86 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 49.1 12.19 1 48 1 0
#> 96 14.54 1 33 0 1
#> 111.1 17.45 1 47 0 1
#> 195 11.76 1 NA 1 0
#> 23.1 16.92 1 61 0 0
#> 199 19.81 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 40.1 18.00 1 28 1 0
#> 36 21.19 1 48 0 1
#> 61 10.12 1 36 0 1
#> 99 21.19 1 38 0 1
#> 85 16.44 1 36 0 0
#> 41 18.02 1 40 1 0
#> 55 19.34 1 69 0 1
#> 195.1 11.76 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 181 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 23.2 16.92 1 61 0 0
#> 40.2 18.00 1 28 1 0
#> 181.1 16.46 1 45 0 1
#> 113.1 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 10.1 10.53 1 34 0 0
#> 32.1 20.90 1 37 1 0
#> 167.2 15.55 1 56 1 0
#> 78 23.88 1 43 0 0
#> 177.1 12.53 1 75 0 0
#> 171 16.57 1 41 0 1
#> 70.1 7.38 1 30 1 0
#> 42 12.43 1 49 0 1
#> 23.3 16.92 1 61 0 0
#> 117.2 17.46 1 26 0 1
#> 32.2 20.90 1 37 1 0
#> 52.1 10.42 1 52 0 1
#> 125.1 15.65 1 67 1 0
#> 8 18.43 1 32 0 0
#> 150 20.33 1 48 0 0
#> 167.3 15.55 1 56 1 0
#> 166 19.98 1 48 0 0
#> 127.1 3.53 1 62 0 1
#> 192.1 16.44 1 31 1 0
#> 184 17.77 1 38 0 0
#> 93.1 10.33 1 52 0 1
#> 36.1 21.19 1 48 0 1
#> 129 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 14 12.89 1 21 0 0
#> 40.3 18.00 1 28 1 0
#> 69.3 23.23 1 25 0 1
#> 29 15.45 1 68 1 0
#> 134.1 17.81 1 47 1 0
#> 144 24.00 0 28 0 1
#> 9 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 163.1 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 46 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 34.1 24.00 0 36 0 0
#> 34.2 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 33 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 2 24.00 0 9 0 0
#> 73 24.00 0 NA 0 1
#> 64 24.00 0 43 0 0
#> 132 24.00 0 55 0 0
#> 12 24.00 0 63 0 0
#> 20 24.00 0 46 1 0
#> 186.1 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 144.1 24.00 0 28 0 1
#> 119 24.00 0 17 0 0
#> 119.1 24.00 0 17 0 0
#> 2.1 24.00 0 9 0 0
#> 72 24.00 0 40 0 1
#> 48 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 2.2 24.00 0 9 0 0
#> 12.1 24.00 0 63 0 0
#> 27 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 71 24.00 0 51 0 0
#> 27.1 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 144.2 24.00 0 28 0 1
#> 186.2 24.00 0 45 1 0
#> 94.1 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 1.1 24.00 0 23 1 0
#> 193.1 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 144.3 24.00 0 28 0 1
#> 12.2 24.00 0 63 0 0
#> 122 24.00 0 66 0 0
#> 198.1 24.00 0 66 0 1
#> 193.2 24.00 0 45 0 1
#> 163.2 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 132.1 24.00 0 55 0 0
#> 196 24.00 0 19 0 0
#> 151.1 24.00 0 42 0 0
#> 9.1 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 116.1 24.00 0 58 0 1
#> 198.2 24.00 0 66 0 1
#> 152 24.00 0 36 0 1
#> 176.1 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 198.3 24.00 0 66 0 1
#> 87.1 24.00 0 27 0 0
#> 176.2 24.00 0 43 0 1
#> 122.1 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 2.3 24.00 0 9 0 0
#> 200 24.00 0 64 0 0
#> 185.1 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 54 24.00 0 53 1 0
#> 87.2 24.00 0 27 0 0
#> 83 24.00 0 6 0 0
#> 31.1 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.745 NA NA NA
#> 2 age, Cure model 0.00928 NA NA NA
#> 3 grade_ii, Cure model 0.696 NA NA NA
#> 4 grade_iii, Cure model 0.836 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00148 NA NA NA
#> 2 grade_ii, Survival model 0.306 NA NA NA
#> 3 grade_iii, Survival model 0.0371 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.745248 0.009279 0.696029 0.835786
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 257.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.745248488 0.009278938 0.696028708 0.835785995
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001483094 0.306144029 0.037095854
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.54724998 0.96897990 0.21936160 0.82535471 0.87366414 0.48476816
#> [7] 0.92164532 0.98450678 0.78459262 0.67757414 0.33338541 0.49384193
#> [13] 0.27300388 0.65189924 0.18476747 0.08033168 0.83349967 0.26209495
#> [19] 0.08033168 0.64319004 0.12459213 0.94547873 0.76821140 0.53827998
#> [25] 0.88966308 0.17246545 0.03052954 0.96113102 0.69442634 0.19700318
#> [31] 0.49384193 0.35329319 0.85762967 0.08033168 0.70289804 0.77640424
#> [37] 0.96897990 0.30294647 0.91363818 0.70289804 0.61737347 0.74367303
#> [43] 0.55620175 0.12459213 0.19700318 0.35329319 0.31312102 0.42162117
#> [49] 0.74367303 0.52045334 0.45762813 0.39242990 0.92962204 0.14862405
#> [55] 0.38262329 0.83349967 0.76000768 0.52045334 0.55620175 0.93756468
#> [61] 0.42162117 0.23056373 0.90562730 0.23056373 0.61737347 0.41196189
#> [67] 0.37278535 0.65189924 0.59981876 0.66898753 0.55620175 0.42162117
#> [73] 0.59981876 0.14862405 0.84956679 0.80095999 0.85762967 0.27300388
#> [79] 0.70289804 0.01194696 0.80095999 0.59094763 0.94547873 0.81720226
#> [85] 0.55620175 0.49384193 0.27300388 0.87366414 0.67757414 0.40220165
#> [91] 0.32326491 0.70289804 0.34334993 0.98450678 0.61737347 0.47567008
#> [97] 0.88966308 0.23056373 0.06524148 0.04834741 0.79277764 0.42162117
#> [103] 0.08033168 0.73544434 0.45762813 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 45 25 153 56 52 110 187 127 155 125 158 117 32
#> 17.42 6.32 21.33 12.21 10.42 17.56 9.92 3.53 13.08 15.65 20.14 17.46 20.90
#> 79 66 69 49 90 69.1 5 92 70 13 30 93 169
#> 16.23 22.13 23.23 12.19 20.94 23.23 16.43 22.92 7.38 14.34 17.43 10.33 22.41
#> 168 77 6 197 117.1 170 10 69.2 167 81 25.1 190 101
#> 23.72 7.27 15.64 21.60 17.46 19.54 10.53 23.23 15.55 14.06 6.32 20.81 9.97
#> 167.1 192 133 23 92.1 197.1 170.1 128 40 133.1 111 134 97
#> 15.55 16.44 14.65 16.92 22.92 21.60 19.54 20.35 18.00 14.65 17.45 17.81 19.14
#> 183 113 76 49.1 96 111.1 23.1 149 40.1 36 61 99 85
#> 9.24 22.86 19.22 12.19 14.54 17.45 16.92 8.37 18.00 21.19 10.12 21.19 16.44
#> 41 55 79.1 181 26 23.2 40.2 181.1 113.1 159 177 10.1 32.1
#> 18.02 19.34 16.23 16.46 15.77 16.92 18.00 16.46 22.86 10.55 12.53 10.53 20.90
#> 167.2 78 177.1 171 70.1 42 23.3 117.2 32.2 52.1 125.1 8 150
#> 15.55 23.88 12.53 16.57 7.38 12.43 16.92 17.46 20.90 10.42 15.65 18.43 20.33
#> 167.3 166 127.1 192.1 184 93.1 36.1 129 164 14 40.3 69.3 29
#> 15.55 19.98 3.53 16.44 17.77 10.33 21.19 23.41 23.60 12.89 18.00 23.23 15.45
#> 134.1 144 9 193 163 34 137 75 1 163.1 94 46 21
#> 17.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 34.1 34.2 87 62 103 33 135 2 64 132 12 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 151 144.1 119 119.1 2.1 72 48 38 31 176 2.2 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 185 98 71 27.1 198 144.2 186.2 94.1 35 19 1.1 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 137.1 120 112 144.3 12.2 122 198.1 193.2 163.2 116 132.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 9.1 75.1 116.1 198.2 152 176.1 118 46.1 198.3 87.1 176.2 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 2.3 200 185.1 28 54 87.2 83 31.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[53]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004591025 0.731447204 0.394522451
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.054172332 0.002707048 0.184201050
#> grade_iii, Cure model
#> -0.003372612
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 10 10.53 1 34 0 0
#> 113 22.86 1 34 0 0
#> 92 22.92 1 47 0 1
#> 184 17.77 1 38 0 0
#> 32 20.90 1 37 1 0
#> 99 21.19 1 38 0 1
#> 189 10.51 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 8 18.43 1 32 0 0
#> 68 20.62 1 44 0 0
#> 29 15.45 1 68 1 0
#> 157 15.10 1 47 0 0
#> 158 20.14 1 74 1 0
#> 127 3.53 1 62 0 1
#> 106 16.67 1 49 1 0
#> 111 17.45 1 47 0 1
#> 177 12.53 1 75 0 0
#> 63 22.77 1 31 1 0
#> 108 18.29 1 39 0 1
#> 164 23.60 1 76 0 1
#> 40 18.00 1 28 1 0
#> 59 10.16 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 179 18.63 1 42 0 0
#> 192 16.44 1 31 1 0
#> 92.1 22.92 1 47 0 1
#> 106.1 16.67 1 49 1 0
#> 36 21.19 1 48 0 1
#> 40.1 18.00 1 28 1 0
#> 117 17.46 1 26 0 1
#> 108.1 18.29 1 39 0 1
#> 195 11.76 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 26 15.77 1 49 0 1
#> 25 6.32 1 34 1 0
#> 159 10.55 1 50 0 1
#> 29.1 15.45 1 68 1 0
#> 81 14.06 1 34 0 0
#> 60 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 123 13.00 1 44 1 0
#> 184.1 17.77 1 38 0 0
#> 78.1 23.88 1 43 0 0
#> 57 14.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 25.1 6.32 1 34 1 0
#> 10.1 10.53 1 34 0 0
#> 63.1 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 8.1 18.43 1 32 0 0
#> 125 15.65 1 67 1 0
#> 25.2 6.32 1 34 1 0
#> 15 22.68 1 48 0 0
#> 184.2 17.77 1 38 0 0
#> 145 10.07 1 65 1 0
#> 77 7.27 1 67 0 1
#> 85 16.44 1 36 0 0
#> 192.1 16.44 1 31 1 0
#> 128 20.35 1 35 0 1
#> 15.1 22.68 1 48 0 0
#> 61 10.12 1 36 0 1
#> 77.1 7.27 1 67 0 1
#> 168 23.72 1 70 0 0
#> 169 22.41 1 46 0 0
#> 145.1 10.07 1 65 1 0
#> 63.2 22.77 1 31 1 0
#> 99.1 21.19 1 38 0 1
#> 99.2 21.19 1 38 0 1
#> 149 8.37 1 33 1 0
#> 59.1 10.16 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 55 19.34 1 69 0 1
#> 92.2 22.92 1 47 0 1
#> 86.1 23.81 1 58 0 1
#> 133 14.65 1 57 0 0
#> 110 17.56 1 65 0 1
#> 168.1 23.72 1 70 0 0
#> 177.1 12.53 1 75 0 0
#> 134 17.81 1 47 1 0
#> 50 10.02 1 NA 1 0
#> 177.2 12.53 1 75 0 0
#> 5 16.43 1 51 0 1
#> 110.1 17.56 1 65 0 1
#> 154 12.63 1 20 1 0
#> 43.1 12.10 1 61 0 1
#> 134.1 17.81 1 47 1 0
#> 105 19.75 1 60 0 0
#> 108.2 18.29 1 39 0 1
#> 52 10.42 1 52 0 1
#> 197 21.60 1 69 1 0
#> 195.1 11.76 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 4 17.64 1 NA 0 1
#> 133.1 14.65 1 57 0 0
#> 125.1 15.65 1 67 1 0
#> 45 17.42 1 54 0 1
#> 91 5.33 1 61 0 1
#> 96.1 14.54 1 33 0 1
#> 50.1 10.02 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 25.3 6.32 1 34 1 0
#> 39 15.59 1 37 0 1
#> 197.1 21.60 1 69 1 0
#> 78.2 23.88 1 43 0 0
#> 179.1 18.63 1 42 0 0
#> 105.1 19.75 1 60 0 0
#> 169.1 22.41 1 46 0 0
#> 168.2 23.72 1 70 0 0
#> 8.2 18.43 1 32 0 0
#> 60.1 13.15 1 38 1 0
#> 168.3 23.72 1 70 0 0
#> 112 24.00 0 61 0 0
#> 34 24.00 0 36 0 0
#> 19 24.00 0 57 0 1
#> 12 24.00 0 63 0 0
#> 17 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 191 24.00 0 60 0 1
#> 144 24.00 0 28 0 1
#> 11 24.00 0 42 0 1
#> 34.1 24.00 0 36 0 0
#> 62 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 34.2 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 173 24.00 0 19 0 1
#> 34.3 24.00 0 36 0 0
#> 193 24.00 0 45 0 1
#> 193.1 24.00 0 45 0 1
#> 198 24.00 0 66 0 1
#> 94 24.00 0 51 0 1
#> 144.1 24.00 0 28 0 1
#> 73 24.00 0 NA 0 1
#> 46 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 126 24.00 0 48 0 0
#> 94.1 24.00 0 51 0 1
#> 116 24.00 0 58 0 1
#> 126.1 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 95.1 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 174 24.00 0 49 1 0
#> 73.1 24.00 0 NA 0 1
#> 98 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 126.2 24.00 0 48 0 0
#> 73.2 24.00 0 NA 0 1
#> 186 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 200.1 24.00 0 64 0 0
#> 22 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 73.3 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 33 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 198.2 24.00 0 66 0 1
#> 83 24.00 0 6 0 0
#> 1 24.00 0 23 1 0
#> 193.2 24.00 0 45 0 1
#> 72 24.00 0 40 0 1
#> 193.3 24.00 0 45 0 1
#> 19.1 24.00 0 57 0 1
#> 115.1 24.00 0 NA 1 0
#> 146 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 137 24.00 0 45 1 0
#> 193.4 24.00 0 45 0 1
#> 20 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 178.1 24.00 0 52 1 0
#> 83.1 24.00 0 6 0 0
#> 72.1 24.00 0 40 0 1
#> 64.1 24.00 0 43 0 0
#> 3 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 33.1 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 173.1 24.00 0 19 0 1
#> 137.1 24.00 0 45 1 0
#> 174.1 24.00 0 49 1 0
#> 191.1 24.00 0 60 0 1
#> 104 24.00 0 50 1 0
#> 33.2 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 132.1 24.00 0 55 0 0
#> 198.3 24.00 0 66 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0542 NA NA NA
#> 2 age, Cure model 0.00271 NA NA NA
#> 3 grade_ii, Cure model 0.184 NA NA NA
#> 4 grade_iii, Cure model -0.00337 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00459 NA NA NA
#> 2 grade_ii, Survival model 0.731 NA NA NA
#> 3 grade_iii, Survival model 0.395 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.054172 0.002707 0.184201 -0.003373
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 254.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.054172332 0.002707048 0.184201050 -0.003372612
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004591025 0.731447204 0.394522451
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.87951780 0.16705185 0.13081943 0.53215174 0.33707103 0.28895104
#> [7] 0.01338791 0.42639242 0.34706847 0.71152625 0.72857753 0.36709535
#> [13] 0.99212457 0.61487641 0.58727331 0.83012801 0.18027587 0.45605189
#> [19] 0.11658923 0.49504590 0.75435631 0.40657395 0.63281895 0.13081943
#> [25] 0.61487641 0.28895104 0.49504590 0.57804042 0.45605189 0.66783256
#> [31] 0.28895104 0.67668736 0.95305792 0.87125478 0.71152625 0.77999845
#> [37] 0.78857816 0.85477921 0.80537332 0.53215174 0.01338791 0.77143236
#> [43] 0.48525550 0.95305792 0.87951780 0.18027587 0.27818698 0.42639242
#> [49] 0.68552081 0.95305792 0.21195176 0.53215174 0.91253516 0.93692229
#> [55] 0.63281895 0.63281895 0.35711888 0.21195176 0.90428270 0.93692229
#> [61] 0.06905332 0.23408270 0.91253516 0.18027587 0.28895104 0.28895104
#> [67] 0.92880669 0.04526800 0.39662711 0.13081943 0.04526800 0.73717329
#> [73] 0.55962973 0.06905332 0.83012801 0.51382474 0.83012801 0.65900593
#> [79] 0.55962973 0.81375383 0.85477921 0.51382474 0.37694351 0.45605189
#> [85] 0.89601080 0.25662061 0.81375383 0.73717329 0.68552081 0.59647788
#> [91] 0.98424187 0.75435631 0.60566008 0.95305792 0.70283984 0.25662061
#> [97] 0.01338791 0.40657395 0.37694351 0.23408270 0.06905332 0.42639242
#> [103] 0.78857816 0.06905332 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 10 113 92 184 32 99 78 8 68 29 157 158 127
#> 10.53 22.86 22.92 17.77 20.90 21.19 23.88 18.43 20.62 15.45 15.10 20.14 3.53
#> 106 111 177 63 108 164 40 96 179 192 92.1 106.1 36
#> 16.67 17.45 12.53 22.77 18.29 23.60 18.00 14.54 18.63 16.44 22.92 16.67 21.19
#> 40.1 117 108.1 100 36.1 26 25 159 29.1 81 60 43 123
#> 18.00 17.46 18.29 16.07 21.19 15.77 6.32 10.55 15.45 14.06 13.15 12.10 13.00
#> 184.1 78.1 57 41 25.1 10.1 63.1 139 8.1 125 25.2 15 184.2
#> 17.77 23.88 14.46 18.02 6.32 10.53 22.77 21.49 18.43 15.65 6.32 22.68 17.77
#> 145 77 85 192.1 128 15.1 61 77.1 168 169 145.1 63.2 99.1
#> 10.07 7.27 16.44 16.44 20.35 22.68 10.12 7.27 23.72 22.41 10.07 22.77 21.19
#> 99.2 149 86 55 92.2 86.1 133 110 168.1 177.1 134 177.2 5
#> 21.19 8.37 23.81 19.34 22.92 23.81 14.65 17.56 23.72 12.53 17.81 12.53 16.43
#> 110.1 154 43.1 134.1 105 108.2 52 197 154.1 133.1 125.1 45 91
#> 17.56 12.63 12.10 17.81 19.75 18.29 10.42 21.60 12.63 14.65 15.65 17.42 5.33
#> 96.1 23 25.3 39 197.1 78.2 179.1 105.1 169.1 168.2 8.2 60.1 168.3
#> 14.54 16.92 6.32 15.59 21.60 23.88 18.63 19.75 22.41 23.72 18.43 13.15 23.72
#> 112 34 19 12 17 64 191 144 11 34.1 62 152 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 182 34.2 173 34.3 193 193.1 198 94 144.1 46 198.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 116 126.1 95 172 95.1 185 46.1 160 44 174 98 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.2 186 200 178 7 200.1 22 47 132 148 33 54 198.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 1 193.2 72 193.3 19.1 146 48 147 137 193.4 20 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 83.1 72.1 64.1 3 103 33.1 53 173.1 137.1 174.1 191.1 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.2 163 132.1 198.3
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[54]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00618098 0.69234994 0.42787812
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.77763546 0.01484763 0.10950600
#> grade_iii, Cure model
#> 0.75034442
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 158 20.14 1 74 1 0
#> 106 16.67 1 49 1 0
#> 136 21.83 1 43 0 1
#> 177 12.53 1 75 0 0
#> 66 22.13 1 53 0 0
#> 70 7.38 1 30 1 0
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 10 10.53 1 34 0 0
#> 51 18.23 1 83 0 1
#> 6 15.64 1 39 0 0
#> 60 13.15 1 38 1 0
#> 164 23.60 1 76 0 1
#> 175 21.91 1 43 0 0
#> 16 8.71 1 71 0 1
#> 129 23.41 1 53 1 0
#> 29 15.45 1 68 1 0
#> 78 23.88 1 43 0 0
#> 58 19.34 1 39 0 0
#> 136.1 21.83 1 43 0 1
#> 199 19.81 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 37 12.52 1 57 1 0
#> 125 15.65 1 67 1 0
#> 155 13.08 1 26 0 0
#> 111 17.45 1 47 0 1
#> 99 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 179 18.63 1 42 0 0
#> 111.1 17.45 1 47 0 1
#> 25 6.32 1 34 1 0
#> 43 12.10 1 61 0 1
#> 184 17.77 1 38 0 0
#> 85 16.44 1 36 0 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 99.1 21.19 1 38 0 1
#> 16.1 8.71 1 71 0 1
#> 4 17.64 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 43.1 12.10 1 61 0 1
#> 111.2 17.45 1 47 0 1
#> 45 17.42 1 54 0 1
#> 45.1 17.42 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 41.1 18.02 1 40 1 0
#> 168 23.72 1 70 0 0
#> 51.1 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 189 10.51 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 29.1 15.45 1 68 1 0
#> 55 19.34 1 69 0 1
#> 180 14.82 1 37 0 0
#> 113 22.86 1 34 0 0
#> 177.1 12.53 1 75 0 0
#> 90 20.94 1 50 0 1
#> 5 16.43 1 51 0 1
#> 42 12.43 1 49 0 1
#> 136.2 21.83 1 43 0 1
#> 134 17.81 1 47 1 0
#> 183 9.24 1 67 1 0
#> 157 15.10 1 47 0 0
#> 78.1 23.88 1 43 0 0
#> 79 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 18 15.21 1 49 1 0
#> 29.2 15.45 1 68 1 0
#> 89 11.44 1 NA 0 0
#> 140 12.68 1 59 1 0
#> 199.1 19.81 1 NA 0 1
#> 16.2 8.71 1 71 0 1
#> 101 9.97 1 10 0 1
#> 170 19.54 1 43 0 1
#> 79.1 16.23 1 54 1 0
#> 159 10.55 1 50 0 1
#> 168.1 23.72 1 70 0 0
#> 167 15.55 1 56 1 0
#> 24 23.89 1 38 0 0
#> 168.2 23.72 1 70 0 0
#> 150 20.33 1 48 0 0
#> 100 16.07 1 60 0 0
#> 41.2 18.02 1 40 1 0
#> 56 12.21 1 60 0 0
#> 51.2 18.23 1 83 0 1
#> 129.1 23.41 1 53 1 0
#> 30.1 17.43 1 78 0 0
#> 155.1 13.08 1 26 0 0
#> 189.1 10.51 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 6.1 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 8 18.43 1 32 0 0
#> 133 14.65 1 57 0 0
#> 189.2 10.51 1 NA 1 0
#> 189.3 10.51 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 10.1 10.53 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 61 10.12 1 36 0 1
#> 32 20.90 1 37 1 0
#> 130 16.47 1 53 0 1
#> 56.1 12.21 1 60 0 0
#> 181 16.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 43.2 12.10 1 61 0 1
#> 10.2 10.53 1 34 0 0
#> 51.3 18.23 1 83 0 1
#> 5.1 16.43 1 51 0 1
#> 183.1 9.24 1 67 1 0
#> 87 24.00 0 27 0 0
#> 160 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 38 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 73 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#> 160.1 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 161 24.00 0 45 0 0
#> 22 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 9 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 95.1 24.00 0 68 0 1
#> 38.2 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 95.2 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 12.1 24.00 0 63 0 0
#> 2 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 20 24.00 0 46 1 0
#> 65 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 80.1 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 83.1 24.00 0 6 0 0
#> 191 24.00 0 60 0 1
#> 112 24.00 0 61 0 0
#> 196.1 24.00 0 19 0 0
#> 193 24.00 0 45 0 1
#> 162 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 46.2 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 33.2 24.00 0 53 0 0
#> 152.1 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 62.1 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 87.1 24.00 0 27 0 0
#> 165 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 146 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 120 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 1 24.00 0 23 1 0
#> 1.1 24.00 0 23 1 0
#> 144.1 24.00 0 28 0 1
#> 19 24.00 0 57 0 1
#> 147 24.00 0 76 1 0
#> 22.2 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 35 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 73.1 24.00 0 NA 0 1
#> 22.3 24.00 0 52 1 0
#> 142.1 24.00 0 53 0 0
#> 84.1 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 67.1 24.00 0 25 0 0
#> 160.2 24.00 0 31 1 0
#> 73.2 24.00 0 NA 0 1
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 65.1 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.778 NA NA NA
#> 2 age, Cure model 0.0148 NA NA NA
#> 3 grade_ii, Cure model 0.110 NA NA NA
#> 4 grade_iii, Cure model 0.750 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00618 NA NA NA
#> 2 grade_ii, Survival model 0.692 NA NA NA
#> 3 grade_iii, Survival model 0.428 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77764 0.01485 0.10951 0.75034
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77763546 0.01484763 0.10950600 0.75034442
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00618098 0.69234994 0.42787812
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.23815326 0.48733687 0.14372005 0.77233373 0.12026213 0.97312927
#> [7] 0.68838438 0.37010782 0.86397409 0.32987023 0.58430037 0.70730235
#> [13] 0.06286689 0.13186910 0.93710720 0.07611564 0.62274828 0.01316877
#> [19] 0.25864897 0.14372005 0.96409995 0.79068633 0.57468262 0.71670048
#> [25] 0.41916624 0.18614234 0.69783121 0.29898153 0.41916624 0.99107684
#> [31] 0.82741557 0.40923883 0.51675743 0.27883422 0.27883422 0.18614234
#> [37] 0.93710720 0.75414151 0.82741557 0.41916624 0.46768700 0.46768700
#> [43] 0.10896046 0.37010782 0.03113951 0.32987023 0.44795546 0.75414151
#> [49] 0.62274828 0.25864897 0.66946458 0.09740497 0.77233373 0.20688790
#> [55] 0.52657416 0.79987307 0.14372005 0.39936158 0.91903026 0.66005139
#> [61] 0.01316877 0.54593941 0.60351196 0.65067192 0.62274828 0.74481652
#> [67] 0.93710720 0.90069495 0.24843828 0.54593941 0.85476958 0.03113951
#> [73] 0.61316133 0.00371766 0.03113951 0.22774934 0.56501296 0.37010782
#> [79] 0.80904579 0.32987023 0.07611564 0.44795546 0.71670048 0.98210362
#> [85] 0.58430037 0.17519726 0.30931186 0.67890491 0.73544605 0.86397409
#> [91] 0.30931186 0.89145928 0.21746607 0.49716755 0.80904579 0.50697777
#> [97] 0.90988894 0.82741557 0.86397409 0.32987023 0.52657416 0.91903026
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 158 106 136 177 66 70 96 41 10 51 6 60 164
#> 20.14 16.67 21.83 12.53 22.13 7.38 14.54 18.02 10.53 18.23 15.64 13.15 23.60
#> 175 16 129 29 78 58 136.1 149 37 125 155 111 99
#> 21.91 8.71 23.41 15.45 23.88 19.34 21.83 8.37 12.52 15.65 13.08 17.45 21.19
#> 81 179 111.1 25 43 184 85 97 97.1 99.1 16.1 154 43.1
#> 14.06 18.63 17.45 6.32 12.10 17.77 16.44 19.14 19.14 21.19 8.71 12.63 12.10
#> 111.2 45 45.1 194 41.1 168 51.1 30 154.1 29.1 55 180 113
#> 17.45 17.42 17.42 22.40 18.02 23.72 18.23 17.43 12.63 15.45 19.34 14.82 22.86
#> 177.1 90 5 42 136.2 134 183 157 78.1 79 39 18 29.2
#> 12.53 20.94 16.43 12.43 21.83 17.81 9.24 15.10 23.88 16.23 15.59 15.21 15.45
#> 140 16.2 101 170 79.1 159 168.1 167 24 168.2 150 100 41.2
#> 12.68 8.71 9.97 19.54 16.23 10.55 23.72 15.55 23.89 23.72 20.33 16.07 18.02
#> 56 51.2 129.1 30.1 155.1 77 6.1 139 8 133 123 10.1 8.1
#> 12.21 18.23 23.41 17.43 13.08 7.27 15.64 21.49 18.43 14.65 13.00 10.53 18.43
#> 61 32 130 56.1 181 187 43.2 10.2 51.3 5.1 183.1 87 160
#> 10.12 20.90 16.47 12.21 16.46 9.92 12.10 10.53 18.23 16.43 9.24 24.00 24.00
#> 118 80 46 84 38 74 83 152 160.1 103 161 22 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 38.1 46.1 33 12 9 103.1 172 33.1 95 95.1 38.2 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.2 141 131 12.1 2 151 20 65 142 121 48 62 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 135 83.1 191 112 196.1 193 162 118.1 46.2 3 17 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.2 152.1 44 62.1 122 87.1 165 116 146 144 120 174 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 144.1 19 147 22.2 82 35 126 22.3 142.1 84.1 67 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.2 27 119 65.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[55]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0000171327 0.7427343338 0.4507561034
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.8843129 0.0167637 -0.2255385
#> grade_iii, Cure model
#> 1.0775018
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 59 10.16 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 23 16.92 1 61 0 0
#> 170 19.54 1 43 0 1
#> 190 20.81 1 42 1 0
#> 159 10.55 1 50 0 1
#> 32 20.90 1 37 1 0
#> 195 11.76 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 199 19.81 1 NA 0 1
#> 85 16.44 1 36 0 0
#> 166 19.98 1 48 0 0
#> 76 19.22 1 54 0 1
#> 166.1 19.98 1 48 0 0
#> 155 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 60 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 68 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 106 16.67 1 49 1 0
#> 30 17.43 1 78 0 0
#> 90 20.94 1 50 0 1
#> 6 15.64 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 89 11.44 1 NA 0 0
#> 32.1 20.90 1 37 1 0
#> 10 10.53 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 195.1 11.76 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 89.1 11.44 1 NA 0 0
#> 56 12.21 1 60 0 0
#> 166.2 19.98 1 48 0 0
#> 52 10.42 1 52 0 1
#> 125 15.65 1 67 1 0
#> 4 17.64 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 37 12.52 1 57 1 0
#> 110 17.56 1 65 0 1
#> 194 22.40 1 38 0 1
#> 105 19.75 1 60 0 0
#> 149 8.37 1 33 1 0
#> 79 16.23 1 54 1 0
#> 89.2 11.44 1 NA 0 0
#> 124 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 42 12.43 1 49 0 1
#> 169 22.41 1 46 0 0
#> 89.3 11.44 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 25 6.32 1 34 1 0
#> 150 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 93.1 10.33 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 170.1 19.54 1 43 0 1
#> 51 18.23 1 83 0 1
#> 100 16.07 1 60 0 0
#> 88 18.37 1 47 0 0
#> 49 12.19 1 48 1 0
#> 128 20.35 1 35 0 1
#> 168 23.72 1 70 0 0
#> 194.1 22.40 1 38 0 1
#> 130.1 16.47 1 53 0 1
#> 15 22.68 1 48 0 0
#> 60.1 13.15 1 38 1 0
#> 32.2 20.90 1 37 1 0
#> 100.1 16.07 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 8 18.43 1 32 0 0
#> 88.1 18.37 1 47 0 0
#> 10.1 10.53 1 34 0 0
#> 168.1 23.72 1 70 0 0
#> 45 17.42 1 54 0 1
#> 60.2 13.15 1 38 1 0
#> 128.1 20.35 1 35 0 1
#> 130.2 16.47 1 53 0 1
#> 26 15.77 1 49 0 1
#> 157 15.10 1 47 0 0
#> 101 9.97 1 10 0 1
#> 106.1 16.67 1 49 1 0
#> 155.1 13.08 1 26 0 0
#> 51.1 18.23 1 83 0 1
#> 199.1 19.81 1 NA 0 1
#> 106.2 16.67 1 49 1 0
#> 52.1 10.42 1 52 0 1
#> 105.1 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 99.1 21.19 1 38 0 1
#> 69 23.23 1 25 0 1
#> 128.2 20.35 1 35 0 1
#> 52.2 10.42 1 52 0 1
#> 70 7.38 1 30 1 0
#> 192 16.44 1 31 1 0
#> 89.4 11.44 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 42.1 12.43 1 49 0 1
#> 195.2 11.76 1 NA 1 0
#> 194.2 22.40 1 38 0 1
#> 32.3 20.90 1 37 1 0
#> 99.2 21.19 1 38 0 1
#> 42.2 12.43 1 49 0 1
#> 66 22.13 1 53 0 0
#> 78.1 23.88 1 43 0 0
#> 24 23.89 1 38 0 0
#> 55.1 19.34 1 69 0 1
#> 168.2 23.72 1 70 0 0
#> 127 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 2 24.00 0 9 0 0
#> 31 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 198 24.00 0 66 0 1
#> 147 24.00 0 76 1 0
#> 46 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 161 24.00 0 45 0 0
#> 7 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 7.1 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 2.1 24.00 0 9 0 0
#> 21 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 2.2 24.00 0 9 0 0
#> 200 24.00 0 64 0 0
#> 21.1 24.00 0 47 0 0
#> 46.1 24.00 0 71 0 0
#> 109.1 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 21.2 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 46.2 24.00 0 71 0 0
#> 185 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 176.1 24.00 0 43 0 1
#> 178.1 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 126 24.00 0 48 0 0
#> 137 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 98 24.00 0 34 1 0
#> 82.1 24.00 0 34 0 0
#> 178.2 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 53 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 62.1 24.00 0 71 0 0
#> 109.2 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 186.1 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 185.1 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 75.1 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 38 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 73 24.00 0 NA 0 1
#> 172.1 24.00 0 41 0 0
#> 156.1 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 118 24.00 0 44 1 0
#> 7.2 24.00 0 37 1 0
#> 121 24.00 0 57 1 0
#> 182 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 147.1 24.00 0 76 1 0
#> 152 24.00 0 36 0 1
#> 109.3 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 3 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 48.1 24.00 0 31 1 0
#> 82.2 24.00 0 34 0 0
#> 160.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.884 NA NA NA
#> 2 age, Cure model 0.0168 NA NA NA
#> 3 grade_ii, Cure model -0.226 NA NA NA
#> 4 grade_iii, Cure model 1.08 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0000171 NA NA NA
#> 2 grade_ii, Survival model 0.743 NA NA NA
#> 3 grade_iii, Survival model 0.451 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88431 0.01676 -0.22554 1.07750
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 237.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.8843129 0.0167637 -0.2255385 1.0775018
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0000171327 0.7427343338 0.4507561034
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.52369896 0.64404206 0.50437415 0.39508791 0.90675536 0.35379124
#> [7] 0.29062605 0.70328483 0.45528565 0.55182970 0.45528565 0.83922261
#> [13] 0.30443849 0.81636985 0.89936267 0.40552980 0.80843267 0.65301178
#> [19] 0.62602943 0.34129968 0.76842211 0.76842211 0.35379124 0.91411382
#> [25] 0.70328483 0.04129206 0.88443865 0.45528565 0.92877136 0.76039339
#> [31] 0.95037986 0.85452766 0.61698648 0.23458486 0.48461752 0.97188067
#> [37] 0.72783621 0.67841406 0.86213919 0.21809553 0.79242314 0.98603773
#> [43] 0.44529022 0.13247424 0.95037986 0.80045075 0.50437415 0.58946327
#> [49] 0.73601119 0.57072494 0.89193510 0.41597150 0.08038800 0.23458486
#> [55] 0.67841406 0.20160582 0.81636985 0.35379124 0.73601119 0.52369896
#> [61] 0.56127736 0.57072494 0.91411382 0.08038800 0.63507220 0.81636985
#> [67] 0.41597150 0.67841406 0.75226997 0.78439546 0.96471614 0.65301178
#> [73] 0.83922261 0.58946327 0.65301178 0.92877136 0.48461752 0.60786718
#> [79] 0.30443849 0.15116348 0.41597150 0.92877136 0.97898742 0.70328483
#> [85] 0.16862581 0.86213919 0.23458486 0.35379124 0.30443849 0.86213919
#> [91] 0.27604894 0.04129206 0.01520039 0.52369896 0.08038800 0.99303288
#> [97] 0.18511576 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 58 23 170 190 159 32 197 85 166 76 166.1 155 99
#> 19.34 16.92 19.54 20.81 10.55 20.90 21.60 16.44 19.98 19.22 19.98 13.08 21.19
#> 60 43 68 13 106 30 90 6 6.1 32.1 10 85.1 78
#> 13.15 12.10 20.62 14.34 16.67 17.43 20.94 15.64 15.64 20.90 10.53 16.44 23.88
#> 56 166.2 52 125 93 37 110 194 105 149 79 130 42
#> 12.21 19.98 10.42 15.65 10.33 12.52 17.56 22.40 19.75 8.37 16.23 16.47 12.43
#> 169 133 25 150 164 93.1 57 170.1 51 100 88 49 128
#> 22.41 14.65 6.32 20.33 23.60 10.33 14.46 19.54 18.23 16.07 18.37 12.19 20.35
#> 168 194.1 130.1 15 60.1 32.2 100.1 55 8 88.1 10.1 168.1 45
#> 23.72 22.40 16.47 22.68 13.15 20.90 16.07 19.34 18.43 18.37 10.53 23.72 17.42
#> 60.2 128.1 130.2 26 157 101 106.1 155.1 51.1 106.2 52.1 105.1 40
#> 13.15 20.35 16.47 15.77 15.10 9.97 16.67 13.08 18.23 16.67 10.42 19.75 18.00
#> 99.1 69 128.2 52.2 70 192 92 42.1 194.2 32.3 99.2 42.2 66
#> 21.19 23.23 20.35 10.42 7.38 16.44 22.92 12.43 22.40 20.90 21.19 12.43 22.13
#> 78.1 24 55.1 168.2 127 113 2 31 48 176 138 22 67
#> 23.88 23.89 19.34 23.72 3.53 22.86 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 198 147 46 95 161 7 33 7.1 47 196 2.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 82 109 2.2 200 21.1 46.1 109.1 178 172 64 72 21.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 46.2 185 162 62 176.1 178.1 186 87 126 137 131 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 82.1 178.2 141 75 53 122 34 62.1 109.2 156 186.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 143 84 75.1 160 162.1 161.1 38 112 172.1 156.1 198.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.2 121 182 173 147.1 152 109.3 126.1 83 3 53.1 48.1 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[56]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02111807 0.40463722 -0.01798901
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.387957181 0.008118501 -0.113999958
#> grade_iii, Cure model
#> 0.787811309
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 100 16.07 1 60 0 0
#> 150 20.33 1 48 0 0
#> 101 9.97 1 10 0 1
#> 154 12.63 1 20 1 0
#> 45 17.42 1 54 0 1
#> 134 17.81 1 47 1 0
#> 134.1 17.81 1 47 1 0
#> 181 16.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 108 18.29 1 39 0 1
#> 26 15.77 1 49 0 1
#> 45.1 17.42 1 54 0 1
#> 157 15.10 1 47 0 0
#> 158 20.14 1 74 1 0
#> 101.1 9.97 1 10 0 1
#> 68 20.62 1 44 0 0
#> 45.2 17.42 1 54 0 1
#> 170 19.54 1 43 0 1
#> 25 6.32 1 34 1 0
#> 59 10.16 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 130 16.47 1 53 0 1
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 111 17.45 1 47 0 1
#> 66 22.13 1 53 0 0
#> 85 16.44 1 36 0 0
#> 55 19.34 1 69 0 1
#> 149 8.37 1 33 1 0
#> 5 16.43 1 51 0 1
#> 150.1 20.33 1 48 0 0
#> 169 22.41 1 46 0 0
#> 23 16.92 1 61 0 0
#> 70 7.38 1 30 1 0
#> 197 21.60 1 69 1 0
#> 39 15.59 1 37 0 1
#> 15 22.68 1 48 0 0
#> 180 14.82 1 37 0 0
#> 153 21.33 1 55 1 0
#> 30 17.43 1 78 0 0
#> 167 15.55 1 56 1 0
#> 195 11.76 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 197.1 21.60 1 69 1 0
#> 105 19.75 1 60 0 0
#> 154.1 12.63 1 20 1 0
#> 51 18.23 1 83 0 1
#> 14.1 12.89 1 21 0 0
#> 128 20.35 1 35 0 1
#> 106 16.67 1 49 1 0
#> 192 16.44 1 31 1 0
#> 97 19.14 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 184 17.77 1 38 0 0
#> 45.3 17.42 1 54 0 1
#> 150.2 20.33 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 158.1 20.14 1 74 1 0
#> 129 23.41 1 53 1 0
#> 10.2 10.53 1 34 0 0
#> 167.1 15.55 1 56 1 0
#> 167.2 15.55 1 56 1 0
#> 97.1 19.14 1 65 0 1
#> 51.1 18.23 1 83 0 1
#> 110 17.56 1 65 0 1
#> 32 20.90 1 37 1 0
#> 5.1 16.43 1 51 0 1
#> 105.1 19.75 1 60 0 0
#> 128.1 20.35 1 35 0 1
#> 169.1 22.41 1 46 0 0
#> 69 23.23 1 25 0 1
#> 139 21.49 1 63 1 0
#> 199 19.81 1 NA 0 1
#> 36.1 21.19 1 48 0 1
#> 10.3 10.53 1 34 0 0
#> 26.1 15.77 1 49 0 1
#> 52 10.42 1 52 0 1
#> 93 10.33 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 154.2 12.63 1 20 1 0
#> 177 12.53 1 75 0 0
#> 189.1 10.51 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 125.1 15.65 1 67 1 0
#> 70.1 7.38 1 30 1 0
#> 157.1 15.10 1 47 0 0
#> 70.2 7.38 1 30 1 0
#> 88 18.37 1 47 0 0
#> 99 21.19 1 38 0 1
#> 158.2 20.14 1 74 1 0
#> 194 22.40 1 38 0 1
#> 43 12.10 1 61 0 1
#> 188.1 16.16 1 46 0 1
#> 100.1 16.07 1 60 0 0
#> 167.3 15.55 1 56 1 0
#> 29 15.45 1 68 1 0
#> 30.1 17.43 1 78 0 0
#> 123 13.00 1 44 1 0
#> 190 20.81 1 42 1 0
#> 70.3 7.38 1 30 1 0
#> 164 23.60 1 76 0 1
#> 113 22.86 1 34 0 0
#> 145 10.07 1 65 1 0
#> 123.1 13.00 1 44 1 0
#> 101.2 9.97 1 10 0 1
#> 97.2 19.14 1 65 0 1
#> 116 24.00 0 58 0 1
#> 186 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 148 24.00 0 61 1 0
#> 64 24.00 0 43 0 0
#> 144 24.00 0 28 0 1
#> 38 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 138 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 176 24.00 0 43 0 1
#> 186.1 24.00 0 45 1 0
#> 174.1 24.00 0 49 1 0
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 185 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 44 24.00 0 56 0 0
#> 87 24.00 0 27 0 0
#> 163 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 34 24.00 0 36 0 0
#> 44.1 24.00 0 56 0 0
#> 191 24.00 0 60 0 1
#> 176.1 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 17.1 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 118 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 33.1 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 53 24.00 0 32 0 1
#> 156 24.00 0 50 1 0
#> 185.1 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 141.1 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 174.2 24.00 0 49 1 0
#> 142.1 24.00 0 53 0 0
#> 73.1 24.00 0 NA 0 1
#> 141.2 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 46 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 104 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 160 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 148.1 24.00 0 61 1 0
#> 118.1 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 191.1 24.00 0 60 0 1
#> 98.1 24.00 0 34 1 0
#> 161.1 24.00 0 45 0 0
#> 119 24.00 0 17 0 0
#> 28 24.00 0 67 1 0
#> 116.2 24.00 0 58 0 1
#> 53.1 24.00 0 32 0 1
#> 137.1 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 163.1 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 173.1 24.00 0 19 0 1
#> 48 24.00 0 31 1 0
#> 104.1 24.00 0 50 1 0
#> 20 24.00 0 46 1 0
#> 109 24.00 0 48 0 0
#> 148.2 24.00 0 61 1 0
#> 142.2 24.00 0 53 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.388 NA NA NA
#> 2 age, Cure model 0.00812 NA NA NA
#> 3 grade_ii, Cure model -0.114 NA NA NA
#> 4 grade_iii, Cure model 0.788 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0211 NA NA NA
#> 2 grade_ii, Survival model 0.405 NA NA NA
#> 3 grade_iii, Survival model -0.0180 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.387957 0.008119 -0.114000 0.787811
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.387957181 0.008118501 -0.113999958 0.787811309
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02111807 0.40463722 -0.01798901
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.596760e-01 2.103033e-02 8.121562e-01 5.687065e-01 1.286430e-01
#> [6] 8.376644e-02 8.376644e-02 1.873622e-01 3.081179e-01 6.799527e-02
#> [11] 2.832230e-01 1.286430e-01 4.193673e-01 2.800206e-02 8.121562e-01
#> [16] 1.509911e-02 1.286430e-01 4.302848e-02 9.783362e-01 2.633253e-03
#> [21] 1.779676e-01 2.375694e-01 7.477103e-03 6.750687e-01 1.077464e-01
#> [26] 2.000758e-03 1.970583e-01 4.664844e-02 8.738122e-01 2.166842e-01
#> [31] 2.103033e-02 7.377088e-04 1.600513e-01 8.949968e-01 3.373522e-03
#> [36] 3.343615e-01 4.599381e-04 4.505883e-01 6.254330e-03 1.144079e-01
#> [41] 3.480532e-01 5.339921e-01 3.373522e-03 3.641453e-02 5.687065e-01
#> [46] 7.297196e-02 5.339921e-01 1.699569e-02 1.688984e-01 1.970583e-01
#> [51] 5.049889e-02 4.667889e-01 9.521809e-02 1.286430e-01 2.103033e-02
#> [56] 6.750687e-01 6.380796e-01 2.800206e-02 2.751458e-05 6.750687e-01
#> [61] 3.480532e-01 3.480532e-01 5.049889e-02 7.297196e-02 1.013369e-01
#> [66] 1.165912e-02 2.166842e-01 3.641453e-02 1.699569e-02 7.377088e-04
#> [71] 1.180342e-04 5.146800e-03 7.477103e-03 6.750687e-01 2.832230e-01
#> [76] 7.508896e-01 7.709625e-01 4.832818e-01 5.687065e-01 6.200595e-01
#> [81] 3.081179e-01 8.949968e-01 4.193673e-01 8.949968e-01 6.321760e-02
#> [86] 7.477103e-03 2.800206e-02 1.479593e-03 6.563842e-01 2.375694e-01
#> [91] 2.596760e-01 3.480532e-01 4.041807e-01 1.144079e-01 5.000682e-01
#> [96] 1.333660e-02 8.949968e-01 1.731904e-07 2.600494e-04 7.913932e-01
#> [101] 5.000682e-01 8.121562e-01 5.049889e-02 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 100 150 101 154 45 134 134.1 181 125 108 26 45.1 157
#> 16.07 20.33 9.97 12.63 17.42 17.81 17.81 16.46 15.65 18.29 15.77 17.42 15.10
#> 158 101.1 68 45.2 170 25 136 130 188 36 10 111 66
#> 20.14 9.97 20.62 17.42 19.54 6.32 21.83 16.47 16.16 21.19 10.53 17.45 22.13
#> 85 55 149 5 150.1 169 23 70 197 39 15 180 153
#> 16.44 19.34 8.37 16.43 20.33 22.41 16.92 7.38 21.60 15.59 22.68 14.82 21.33
#> 30 167 14 197.1 105 154.1 51 14.1 128 106 192 97 96
#> 17.43 15.55 12.89 21.60 19.75 12.63 18.23 12.89 20.35 16.67 16.44 19.14 14.54
#> 184 45.3 150.2 10.1 37 158.1 129 10.2 167.1 167.2 97.1 51.1 110
#> 17.77 17.42 20.33 10.53 12.52 20.14 23.41 10.53 15.55 15.55 19.14 18.23 17.56
#> 32 5.1 105.1 128.1 169.1 69 139 36.1 10.3 26.1 52 93 81
#> 20.90 16.43 19.75 20.35 22.41 23.23 21.49 21.19 10.53 15.77 10.42 10.33 14.06
#> 154.2 177 125.1 70.1 157.1 70.2 88 99 158.2 194 43 188.1 100.1
#> 12.63 12.53 15.65 7.38 15.10 7.38 18.37 21.19 20.14 22.40 12.10 16.16 16.07
#> 167.3 29 30.1 123 190 70.3 164 113 145 123.1 101.2 97.2 116
#> 15.55 15.45 17.43 13.00 20.81 7.38 23.60 22.86 10.07 13.00 9.97 19.14 24.00
#> 186 151 75 103 17 132 67 31 141 173 148 64 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 193 138 174 176 186.1 174.1 3 98 185 44 87 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 34 44.1 191 176.1 80 17.1 137 83 33 62 19 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 121 33.1 47 7 53 156 185.1 142 141.1 116.1 174.2 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 122 200 46 54 104 146 160 80.1 21 148.1 118.1 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 135 191.1 98.1 161.1 119 28 116.2 53.1 137.1 147 163.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 48 104.1 20 109 148.2 142.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[57]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006214551 0.687906361 0.598593636
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91308383 0.01366738 0.40583122
#> grade_iii, Cure model
#> 1.29467513
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 96 14.54 1 33 0 1
#> 79 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 41 18.02 1 40 1 0
#> 153 21.33 1 55 1 0
#> 177 12.53 1 75 0 0
#> 56 12.21 1 60 0 0
#> 97 19.14 1 65 0 1
#> 158 20.14 1 74 1 0
#> 60.1 13.15 1 38 1 0
#> 55 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 181 16.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 134 17.81 1 47 1 0
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 108 18.29 1 39 0 1
#> 69 23.23 1 25 0 1
#> 159 10.55 1 50 0 1
#> 113 22.86 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 18 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 15 22.68 1 48 0 0
#> 179 18.63 1 42 0 0
#> 125 15.65 1 67 1 0
#> 107 11.18 1 54 1 0
#> 18.1 15.21 1 49 1 0
#> 169 22.41 1 46 0 0
#> 133 14.65 1 57 0 0
#> 10 10.53 1 34 0 0
#> 24 23.89 1 38 0 0
#> 136 21.83 1 43 0 1
#> 128 20.35 1 35 0 1
#> 111 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 25 6.32 1 34 1 0
#> 76 19.22 1 54 0 1
#> 18.2 15.21 1 49 1 0
#> 37.1 12.52 1 57 1 0
#> 56.1 12.21 1 60 0 0
#> 61.1 10.12 1 36 0 1
#> 130 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 123 13.00 1 44 1 0
#> 129 23.41 1 53 1 0
#> 79.1 16.23 1 54 1 0
#> 63 22.77 1 31 1 0
#> 136.1 21.83 1 43 0 1
#> 108.1 18.29 1 39 0 1
#> 40 18.00 1 28 1 0
#> 169.1 22.41 1 46 0 0
#> 188 16.16 1 46 0 1
#> 18.3 15.21 1 49 1 0
#> 76.1 19.22 1 54 0 1
#> 5 16.43 1 51 0 1
#> 145.1 10.07 1 65 1 0
#> 129.1 23.41 1 53 1 0
#> 168 23.72 1 70 0 0
#> 153.1 21.33 1 55 1 0
#> 166 19.98 1 48 0 0
#> 154 12.63 1 20 1 0
#> 108.2 18.29 1 39 0 1
#> 184 17.77 1 38 0 0
#> 111.1 17.45 1 47 0 1
#> 111.2 17.45 1 47 0 1
#> 63.1 22.77 1 31 1 0
#> 106 16.67 1 49 1 0
#> 96.1 14.54 1 33 0 1
#> 139 21.49 1 63 1 0
#> 16 8.71 1 71 0 1
#> 192 16.44 1 31 1 0
#> 188.1 16.16 1 46 0 1
#> 85 16.44 1 36 0 0
#> 114 13.68 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 105 19.75 1 60 0 0
#> 45 17.42 1 54 0 1
#> 43.1 12.10 1 61 0 1
#> 58 19.34 1 39 0 0
#> 170 19.54 1 43 0 1
#> 123.1 13.00 1 44 1 0
#> 169.2 22.41 1 46 0 0
#> 55.1 19.34 1 69 0 1
#> 45.1 17.42 1 54 0 1
#> 93.1 10.33 1 52 0 1
#> 100 16.07 1 60 0 0
#> 30 17.43 1 78 0 0
#> 4 17.64 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 37.2 12.52 1 57 1 0
#> 92 22.92 1 47 0 1
#> 110 17.56 1 65 0 1
#> 37.3 12.52 1 57 1 0
#> 49 12.19 1 48 1 0
#> 168.1 23.72 1 70 0 0
#> 117 17.46 1 26 0 1
#> 26 15.77 1 49 0 1
#> 69.1 23.23 1 25 0 1
#> 26.1 15.77 1 49 0 1
#> 149 8.37 1 33 1 0
#> 117.1 17.46 1 26 0 1
#> 199.1 19.81 1 NA 0 1
#> 108.3 18.29 1 39 0 1
#> 78 23.88 1 43 0 0
#> 155.1 13.08 1 26 0 0
#> 157 15.10 1 47 0 0
#> 32 20.90 1 37 1 0
#> 160 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 162 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 115 24.00 0 NA 1 0
#> 200 24.00 0 64 0 0
#> 71 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 71.1 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 12.1 24.00 0 63 0 0
#> 138 24.00 0 44 1 0
#> 147.2 24.00 0 76 1 0
#> 67 24.00 0 25 0 0
#> 178 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 7 24.00 0 37 1 0
#> 122 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 102 24.00 0 49 0 0
#> 71.2 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 120 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 22 24.00 0 52 1 0
#> 122.1 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 83.1 24.00 0 6 0 0
#> 142 24.00 0 53 0 0
#> 7.1 24.00 0 37 1 0
#> 17 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 80.1 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 161 24.00 0 45 0 0
#> 65 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 144.1 24.00 0 28 0 1
#> 73.1 24.00 0 NA 0 1
#> 38 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 31.1 24.00 0 36 0 1
#> 72 24.00 0 40 0 1
#> 46 24.00 0 71 0 0
#> 46.1 24.00 0 71 0 0
#> 31.2 24.00 0 36 0 1
#> 38.1 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 151.1 24.00 0 42 0 0
#> 48.1 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 47 24.00 0 38 0 1
#> 115.1 24.00 0 NA 1 0
#> 11 24.00 0 42 0 1
#> 178.1 24.00 0 52 1 0
#> 151.2 24.00 0 42 0 0
#> 148 24.00 0 61 1 0
#> 118.1 24.00 0 44 1 0
#> 143.1 24.00 0 51 0 0
#> 143.2 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 141.2 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 75 24.00 0 21 1 0
#> 146 24.00 0 63 1 0
#> 143.3 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 21 24.00 0 47 0 0
#> 17.1 24.00 0 38 0 1
#> 67.1 24.00 0 25 0 0
#> 1 24.00 0 23 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.913 NA NA NA
#> 2 age, Cure model 0.0137 NA NA NA
#> 3 grade_ii, Cure model 0.406 NA NA NA
#> 4 grade_iii, Cure model 1.29 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00621 NA NA NA
#> 2 grade_ii, Survival model 0.688 NA NA NA
#> 3 grade_iii, Survival model 0.599 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91308 0.01367 0.40583 1.29468
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.2
#> Residual Deviance: 249.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91308383 0.01366738 0.40583122 1.29467513
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006214551 0.687906361 0.598593636
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86068168 0.85073064 0.77086075 0.96660361 0.64858098 0.46301165
#> [7] 0.89938414 0.92232017 0.59545262 0.51548767 0.86068168 0.55334031
#> [13] 0.97512327 0.74723492 0.99591431 0.66293325 0.48463664 0.90414058
#> [19] 0.81511606 0.61161480 0.25871997 0.94922683 0.31142650 0.31142650
#> [25] 0.82042768 0.87046092 0.37199188 0.60354984 0.80974078 0.94481415
#> [31] 0.82042768 0.38628425 0.84566720 0.95360931 0.04678365 0.42618758
#> [37] 0.50548470 0.69710459 0.93593563 0.99180063 0.57898459 0.82042768
#> [43] 0.90414058 0.92232017 0.96660361 0.74117271 0.95798705 0.88022093
#> [49] 0.21638930 0.77086075 0.34358454 0.42618758 0.61161480 0.65581081
#> [55] 0.38628425 0.78220558 0.82042768 0.57898459 0.76501332 0.97512327
#> [61] 0.21638930 0.15200142 0.46301165 0.52508982 0.89461273 0.61161480
#> [67] 0.66993057 0.69710459 0.69710459 0.34358454 0.73503371 0.85073064
#> [73] 0.45105247 0.98349807 0.75322872 0.78220558 0.75322872 0.64122395
#> [79] 0.53463134 0.72263187 0.93593563 0.55334031 0.54409653 0.88022093
#> [85] 0.38628425 0.55334031 0.72263187 0.95798705 0.79332120 0.71623372
#> [91] 0.88980922 0.90414058 0.29448846 0.67690847 0.90414058 0.93141451
#> [97] 0.15200142 0.68376445 0.79888096 0.25871997 0.79888096 0.98766194
#> [103] 0.68376445 0.61161480 0.10304787 0.87046092 0.84059084 0.49522560
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 60 96 79 61 41 153 177 56 97 158 60.1 55 145
#> 13.15 14.54 16.23 10.12 18.02 21.33 12.53 12.21 19.14 20.14 13.15 19.34 10.07
#> 181 91 134 36 37 167 108 69 159 113 113.1 18 155
#> 16.46 5.33 17.81 21.19 12.52 15.55 18.29 23.23 10.55 22.86 22.86 15.21 13.08
#> 15 179 125 107 18.1 169 133 10 24 136 128 111 43
#> 22.68 18.63 15.65 11.18 15.21 22.41 14.65 10.53 23.89 21.83 20.35 17.45 12.10
#> 25 76 18.2 37.1 56.1 61.1 130 93 123 129 79.1 63 136.1
#> 6.32 19.22 15.21 12.52 12.21 10.12 16.47 10.33 13.00 23.41 16.23 22.77 21.83
#> 108.1 40 169.1 188 18.3 76.1 5 145.1 129.1 168 153.1 166 154
#> 18.29 18.00 22.41 16.16 15.21 19.22 16.43 10.07 23.41 23.72 21.33 19.98 12.63
#> 108.2 184 111.1 111.2 63.1 106 96.1 139 16 192 188.1 85 51
#> 18.29 17.77 17.45 17.45 22.77 16.67 14.54 21.49 8.71 16.44 16.16 16.44 18.23
#> 105 45 43.1 58 170 123.1 169.2 55.1 45.1 93.1 100 30 14
#> 19.75 17.42 12.10 19.34 19.54 13.00 22.41 19.34 17.42 10.33 16.07 17.43 12.89
#> 37.2 92 110 37.3 49 168.1 117 26 69.1 26.1 149 117.1 108.3
#> 12.52 22.92 17.56 12.52 12.19 23.72 17.46 15.77 23.23 15.77 8.37 17.46 18.29
#> 78 155.1 157 32 160 144 162 12 191 200 71 182 71.1
#> 23.88 13.08 15.10 20.90 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 141 147 147.1 12.1 138 147.2 67 178 141.1 82 7 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 102 71.2 2 120 83 48 28 22 122.1 103 83.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 17 118 80 152 143 135 80.1 19 161 65 31 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 196 151 31.1 72 46 46.1 31.2 38.1 137 119 151.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 47 11 178.1 151.2 148 118.1 143.1 143.2 3 120.1 2.1 141.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 75 146 143.3 84 174 21 17.1 67.1 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[58]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01173775 0.25531894 0.74134982
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.77372545 0.01104172 0.55847132
#> grade_iii, Cure model
#> 0.81537078
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 190 20.81 1 42 1 0
#> 166 19.98 1 48 0 0
#> 175 21.91 1 43 0 0
#> 76 19.22 1 54 0 1
#> 117 17.46 1 26 0 1
#> 199 19.81 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 50 10.02 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 177 12.53 1 75 0 0
#> 6 15.64 1 39 0 0
#> 50.1 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 167 15.55 1 56 1 0
#> 113 22.86 1 34 0 0
#> 63 22.77 1 31 1 0
#> 25 6.32 1 34 1 0
#> 30 17.43 1 78 0 0
#> 190.1 20.81 1 42 1 0
#> 105 19.75 1 60 0 0
#> 190.2 20.81 1 42 1 0
#> 140 12.68 1 59 1 0
#> 167.1 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 91 5.33 1 61 0 1
#> 183 9.24 1 67 1 0
#> 170 19.54 1 43 0 1
#> 78 23.88 1 43 0 0
#> 187 9.92 1 39 1 0
#> 153.1 21.33 1 55 1 0
#> 63.1 22.77 1 31 1 0
#> 190.3 20.81 1 42 1 0
#> 99 21.19 1 38 0 1
#> 127 3.53 1 62 0 1
#> 171 16.57 1 41 0 1
#> 39 15.59 1 37 0 1
#> 166.1 19.98 1 48 0 0
#> 169 22.41 1 46 0 0
#> 26 15.77 1 49 0 1
#> 101 9.97 1 10 0 1
#> 157 15.10 1 47 0 0
#> 129 23.41 1 53 1 0
#> 158 20.14 1 74 1 0
#> 134 17.81 1 47 1 0
#> 76.1 19.22 1 54 0 1
#> 85 16.44 1 36 0 0
#> 158.1 20.14 1 74 1 0
#> 93.1 10.33 1 52 0 1
#> 187.1 9.92 1 39 1 0
#> 108 18.29 1 39 0 1
#> 114 13.68 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 129.1 23.41 1 53 1 0
#> 96 14.54 1 33 0 1
#> 127.1 3.53 1 62 0 1
#> 43 12.10 1 61 0 1
#> 113.1 22.86 1 34 0 0
#> 23 16.92 1 61 0 0
#> 199.1 19.81 1 NA 0 1
#> 199.2 19.81 1 NA 0 1
#> 187.2 9.92 1 39 1 0
#> 167.2 15.55 1 56 1 0
#> 37 12.52 1 57 1 0
#> 36 21.19 1 48 0 1
#> 93.2 10.33 1 52 0 1
#> 169.1 22.41 1 46 0 0
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 114.1 13.68 1 NA 0 0
#> 170.1 19.54 1 43 0 1
#> 179 18.63 1 42 0 0
#> 76.2 19.22 1 54 0 1
#> 79 16.23 1 54 1 0
#> 40.1 18.00 1 28 1 0
#> 155.1 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 14 12.89 1 21 0 0
#> 188 16.16 1 46 0 1
#> 16 8.71 1 71 0 1
#> 130 16.47 1 53 0 1
#> 63.2 22.77 1 31 1 0
#> 56 12.21 1 60 0 0
#> 25.1 6.32 1 34 1 0
#> 153.2 21.33 1 55 1 0
#> 123 13.00 1 44 1 0
#> 88 18.37 1 47 0 0
#> 43.1 12.10 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 24 23.89 1 38 0 0
#> 127.2 3.53 1 62 0 1
#> 128 20.35 1 35 0 1
#> 106.1 16.67 1 49 1 0
#> 106.2 16.67 1 49 1 0
#> 150 20.33 1 48 0 0
#> 36.2 21.19 1 48 0 1
#> 43.2 12.10 1 61 0 1
#> 10 10.53 1 34 0 0
#> 90 20.94 1 50 0 1
#> 157.1 15.10 1 47 0 0
#> 127.3 3.53 1 62 0 1
#> 171.1 16.57 1 41 0 1
#> 61.1 10.12 1 36 0 1
#> 168 23.72 1 70 0 0
#> 188.1 16.16 1 46 0 1
#> 99.2 21.19 1 38 0 1
#> 69 23.23 1 25 0 1
#> 117.1 17.46 1 26 0 1
#> 97 19.14 1 65 0 1
#> 33 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 17 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 121 24.00 0 57 1 0
#> 198.1 24.00 0 66 0 1
#> 161 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 118.1 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 67 24.00 0 25 0 0
#> 196 24.00 0 19 0 0
#> 152.1 24.00 0 36 0 1
#> 196.1 24.00 0 19 0 0
#> 185 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 11 24.00 0 42 0 1
#> 161.1 24.00 0 45 0 0
#> 161.2 24.00 0 45 0 0
#> 146 24.00 0 63 1 0
#> 200 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 198.2 24.00 0 66 0 1
#> 119 24.00 0 17 0 0
#> 98 24.00 0 34 1 0
#> 73 24.00 0 NA 0 1
#> 80.1 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 193 24.00 0 45 0 1
#> 80.2 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 112 24.00 0 61 0 0
#> 19 24.00 0 57 0 1
#> 7.1 24.00 0 37 1 0
#> 174 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 31 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 137 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 141 24.00 0 44 1 0
#> 11.1 24.00 0 42 0 1
#> 119.1 24.00 0 17 0 0
#> 28 24.00 0 67 1 0
#> 147 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 12 24.00 0 63 0 0
#> 126 24.00 0 48 0 0
#> 116 24.00 0 58 0 1
#> 35.1 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 104 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 72 24.00 0 40 0 1
#> 104.1 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 178 24.00 0 52 1 0
#> 182 24.00 0 35 0 0
#> 176.1 24.00 0 43 0 1
#> 95 24.00 0 68 0 1
#> 73.1 24.00 0 NA 0 1
#> 138 24.00 0 44 1 0
#> 200.1 24.00 0 64 0 0
#> 84.1 24.00 0 39 0 1
#> 87 24.00 0 27 0 0
#> 144 24.00 0 28 0 1
#> 1 24.00 0 23 1 0
#> 193.1 24.00 0 45 0 1
#> 163.1 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 12.1 24.00 0 63 0 0
#> 141.1 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 176.2 24.00 0 43 0 1
#> 44.1 24.00 0 56 0 0
#> 74 24.00 0 43 0 1
#> 87.1 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.774 NA NA NA
#> 2 age, Cure model 0.0110 NA NA NA
#> 3 grade_ii, Cure model 0.558 NA NA NA
#> 4 grade_iii, Cure model 0.815 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0117 NA NA NA
#> 2 grade_ii, Survival model 0.255 NA NA NA
#> 3 grade_iii, Survival model 0.741 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77373 0.01104 0.55847 0.81537
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 251.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77372545 0.01104172 0.55847132 0.81537078
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01173775 0.25531894 0.74134982
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.58107656 0.65608072 0.44277252 0.69345761 0.76202502 0.87869073
#> [7] 0.93138854 0.74442076 0.90134274 0.84132896 0.47539379 0.85095734
#> [13] 0.31441015 0.35600324 0.97460273 0.77335170 0.58107656 0.67143880
#> [19] 0.58107656 0.89685101 0.85095734 0.73844289 0.98214358 0.96693476
#> [25] 0.67907249 0.14658159 0.95530719 0.47539379 0.35600324 0.58107656
#> [31] 0.51549401 0.98587399 0.80073232 0.84617383 0.65608072 0.40886311
#> [37] 0.83646784 0.95136539 0.86487930 0.23992527 0.64044573 0.75617933
#> [43] 0.69345761 0.81637595 0.64044573 0.93138854 0.95530719 0.73223589
#> [49] 0.78455419 0.45963274 0.23992527 0.87411255 0.98587399 0.91463558
#> [55] 0.31441015 0.77897401 0.95530719 0.85095734 0.90580308 0.51549401
#> [61] 0.93138854 0.40886311 0.61516322 0.94345363 0.67907249 0.71953226
#> [67] 0.69345761 0.82151986 0.74442076 0.87869073 0.51549401 0.89232346
#> [73] 0.82661802 0.97079773 0.81121493 0.35600324 0.91023028 0.97460273
#> [79] 0.47539379 0.88778947 0.72590453 0.91463558 0.51549401 0.07727887
#> [85] 0.98587399 0.62378543 0.78455419 0.78455419 0.63215711 0.51549401
#> [91] 0.91463558 0.92719302 0.57173702 0.86487930 0.98587399 0.80073232
#> [97] 0.94345363 0.19999116 0.82661802 0.51549401 0.29133099 0.76202502
#> [103] 0.71312382 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 190 166 175 76 117 155 93 40 177 6 153 167 113
#> 20.81 19.98 21.91 19.22 17.46 13.08 10.33 18.00 12.53 15.64 21.33 15.55 22.86
#> 63 25 30 190.1 105 190.2 140 167.1 51 91 183 170 78
#> 22.77 6.32 17.43 20.81 19.75 20.81 12.68 15.55 18.23 5.33 9.24 19.54 23.88
#> 187 153.1 63.1 190.3 99 127 171 39 166.1 169 26 101 157
#> 9.92 21.33 22.77 20.81 21.19 3.53 16.57 15.59 19.98 22.41 15.77 9.97 15.10
#> 129 158 134 76.1 85 158.1 93.1 187.1 108 106 197 129.1 96
#> 23.41 20.14 17.81 19.22 16.44 20.14 10.33 9.92 18.29 16.67 21.60 23.41 14.54
#> 127.1 43 113.1 23 187.2 167.2 37 36 93.2 169.1 68 61 170.1
#> 3.53 12.10 22.86 16.92 9.92 15.55 12.52 21.19 10.33 22.41 20.62 10.12 19.54
#> 179 76.2 79 40.1 155.1 99.1 14 188 16 130 63.2 56 25.1
#> 18.63 19.22 16.23 18.00 13.08 21.19 12.89 16.16 8.71 16.47 22.77 12.21 6.32
#> 153.2 123 88 43.1 36.1 24 127.2 128 106.1 106.2 150 36.2 43.2
#> 21.33 13.00 18.37 12.10 21.19 23.89 3.53 20.35 16.67 16.67 20.33 21.19 12.10
#> 10 90 157.1 127.3 171.1 61.1 168 188.1 99.2 69 117.1 97 33
#> 10.53 20.94 15.10 3.53 16.57 10.12 23.72 16.16 21.19 23.23 17.46 19.14 24.00
#> 122 118 152 198 17 163 83 121 198.1 161 80 118.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 67 196 152.1 196.1 185 176 84 11 161.1 161.2 146 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 198.2 119 98 80.1 191 193 80.2 7 112 19 7.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 31 44 137 22 102 141 11.1 119.1 28 147 48 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 83.1 12 126 116 35.1 82 104 156 72 104.1 2 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 176.1 95 138 200.1 84.1 87 144 1 193.1 163.1 148 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 174.1 176.2 44.1 74 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[59]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 2.522752e-05 9.179132e-01 3.198614e-01
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.432536951 0.003940632 0.387720822
#> grade_iii, Cure model
#> 0.794423658
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 145 10.07 1 65 1 0
#> 195 11.76 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 70 7.38 1 30 1 0
#> 197 21.60 1 69 1 0
#> 24 23.89 1 38 0 0
#> 181 16.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 85 16.44 1 36 0 0
#> 136 21.83 1 43 0 1
#> 157 15.10 1 47 0 0
#> 123 13.00 1 44 1 0
#> 149 8.37 1 33 1 0
#> 61 10.12 1 36 0 1
#> 183 9.24 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 188.1 16.16 1 46 0 1
#> 60 13.15 1 38 1 0
#> 92 22.92 1 47 0 1
#> 99 21.19 1 38 0 1
#> 123.1 13.00 1 44 1 0
#> 55 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 69 23.23 1 25 0 1
#> 127 3.53 1 62 0 1
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 125 15.65 1 67 1 0
#> 140 12.68 1 59 1 0
#> 128 20.35 1 35 0 1
#> 108 18.29 1 39 0 1
#> 55.1 19.34 1 69 0 1
#> 167 15.55 1 56 1 0
#> 154.1 12.63 1 20 1 0
#> 169 22.41 1 46 0 0
#> 181.1 16.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 91 5.33 1 61 0 1
#> 49 12.19 1 48 1 0
#> 179.1 18.63 1 42 0 0
#> 57 14.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 195.2 11.76 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 107 11.18 1 54 1 0
#> 181.2 16.46 1 45 0 1
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 36 21.19 1 48 0 1
#> 76 19.22 1 54 0 1
#> 184 17.77 1 38 0 0
#> 42 12.43 1 49 0 1
#> 45 17.42 1 54 0 1
#> 60.1 13.15 1 38 1 0
#> 77 7.27 1 67 0 1
#> 195.3 11.76 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 133 14.65 1 57 0 0
#> 149.1 8.37 1 33 1 0
#> 76.1 19.22 1 54 0 1
#> 139 21.49 1 63 1 0
#> 96.1 14.54 1 33 0 1
#> 66 22.13 1 53 0 0
#> 24.1 23.89 1 38 0 0
#> 169.1 22.41 1 46 0 0
#> 61.1 10.12 1 36 0 1
#> 5 16.43 1 51 0 1
#> 149.2 8.37 1 33 1 0
#> 180 14.82 1 37 0 0
#> 96.2 14.54 1 33 0 1
#> 51 18.23 1 83 0 1
#> 36.1 21.19 1 48 0 1
#> 199 19.81 1 NA 0 1
#> 5.1 16.43 1 51 0 1
#> 50 10.02 1 NA 1 0
#> 188.2 16.16 1 46 0 1
#> 59 10.16 1 NA 1 0
#> 123.2 13.00 1 44 1 0
#> 15 22.68 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 199.1 19.81 1 NA 0 1
#> 15.1 22.68 1 48 0 0
#> 63 22.77 1 31 1 0
#> 60.2 13.15 1 38 1 0
#> 86 23.81 1 58 0 1
#> 92.1 22.92 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 167.1 15.55 1 56 1 0
#> 167.2 15.55 1 56 1 0
#> 85.1 16.44 1 36 0 0
#> 39 15.59 1 37 0 1
#> 63.1 22.77 1 31 1 0
#> 86.1 23.81 1 58 0 1
#> 39.1 15.59 1 37 0 1
#> 150 20.33 1 48 0 0
#> 153.1 21.33 1 55 1 0
#> 39.2 15.59 1 37 0 1
#> 81 14.06 1 34 0 0
#> 167.3 15.55 1 56 1 0
#> 25 6.32 1 34 1 0
#> 175 21.91 1 43 0 0
#> 36.2 21.19 1 48 0 1
#> 149.3 8.37 1 33 1 0
#> 60.3 13.15 1 38 1 0
#> 194 22.40 1 38 0 1
#> 16 8.71 1 71 0 1
#> 51.1 18.23 1 83 0 1
#> 177 12.53 1 75 0 0
#> 13.1 14.34 1 54 0 1
#> 39.3 15.59 1 37 0 1
#> 87 24.00 0 27 0 0
#> 135 24.00 0 58 1 0
#> 83 24.00 0 6 0 0
#> 122 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 146 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 162 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 98.1 24.00 0 34 1 0
#> 62 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 75.1 24.00 0 21 1 0
#> 193 24.00 0 45 0 1
#> 191.1 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 35 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 35.1 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 83.1 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 27 24.00 0 63 1 0
#> 193.1 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 95.1 24.00 0 68 0 1
#> 122.1 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 120.1 24.00 0 68 0 1
#> 72 24.00 0 40 0 1
#> 2 24.00 0 9 0 0
#> 173 24.00 0 19 0 1
#> 143 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 116 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 98.2 24.00 0 34 1 0
#> 137 24.00 0 45 1 0
#> 67 24.00 0 25 0 0
#> 151 24.00 0 42 0 0
#> 19 24.00 0 57 0 1
#> 119.1 24.00 0 17 0 0
#> 17 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 151.1 24.00 0 42 0 0
#> 19.1 24.00 0 57 0 1
#> 152 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 146.2 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 163 24.00 0 66 0 0
#> 72.1 24.00 0 40 0 1
#> 3 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 33 24.00 0 53 0 0
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 191.2 24.00 0 60 0 1
#> 193.2 24.00 0 45 0 1
#> 137.1 24.00 0 45 1 0
#> 193.3 24.00 0 45 0 1
#> 163.1 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 115.1 24.00 0 NA 1 0
#> 67.1 24.00 0 25 0 0
#> 148.1 24.00 0 61 1 0
#> 95.2 24.00 0 68 0 1
#> 62.1 24.00 0 71 0 0
#> 19.2 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 48 24.00 0 31 1 0
#> 62.2 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 193.4 24.00 0 45 0 1
#> 34.1 24.00 0 36 0 0
#> 35.2 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.433 NA NA NA
#> 2 age, Cure model 0.00394 NA NA NA
#> 3 grade_ii, Cure model 0.388 NA NA NA
#> 4 grade_iii, Cure model 0.794 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0000252 NA NA NA
#> 2 grade_ii, Survival model 0.918 NA NA NA
#> 3 grade_iii, Survival model 0.320 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.432537 0.003941 0.387721 0.794424
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 255.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.432536951 0.003940632 0.387720822 0.794423658
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 2.522752e-05 9.179132e-01 3.198614e-01
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.92734499 0.86175896 0.61507299 0.97029352 0.30767950 0.02846475
#> [7] 0.55229725 0.76871545 0.57916785 0.29440277 0.71419109 0.82041227
#> [13] 0.94632156 0.91450784 0.93371916 0.61507299 0.79172877 0.13849321
#> [19] 0.35285245 0.82041227 0.43001925 0.42012861 0.11767093 0.99410191
#> [25] 0.47743671 0.89486738 0.64122581 0.84818114 0.40034635 0.49634461
#> [31] 0.43001925 0.68317680 0.86175896 0.22705678 0.55229725 0.84119556
#> [37] 0.98819053 0.90148594 0.47743671 0.76095954 0.43001925 0.33191935
#> [43] 0.35285245 0.90803208 0.55229725 0.53367714 0.73783990 0.35285245
#> [49] 0.45852812 0.52433653 0.88167905 0.54301742 0.79172877 0.97628658
#> [55] 0.84818114 0.72995707 0.94632156 0.45852812 0.32014504 0.73783990
#> [61] 0.26738799 0.02846475 0.22705678 0.91450784 0.59722257 0.94632156
#> [67] 0.72207412 0.73783990 0.50582142 0.35285245 0.59722257 0.61507299
#> [73] 0.82041227 0.20023406 0.88167905 0.20023406 0.17341239 0.79172877
#> [79] 0.07730112 0.13849321 0.68317680 0.68317680 0.57916785 0.64988467
#> [85] 0.17341239 0.07730112 0.64988467 0.41023761 0.33191935 0.64988467
#> [91] 0.78403252 0.68317680 0.98226571 0.28089567 0.35285245 0.94632156
#> [97] 0.79172877 0.25387954 0.94002837 0.50582142 0.87502220 0.76871545
#> [103] 0.64988467 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 145 154 188 70 197 24 181 13 85 136 157 123 149
#> 10.07 12.63 16.16 7.38 21.60 23.89 16.46 14.34 16.44 21.83 15.10 13.00 8.37
#> 61 183 188.1 60 92 99 123.1 55 105 69 127 179 56
#> 10.12 9.24 16.16 13.15 22.92 21.19 13.00 19.34 19.75 23.23 3.53 18.63 12.21
#> 125 140 128 108 55.1 167 154.1 169 181.1 14 91 49 179.1
#> 15.65 12.68 20.35 18.29 19.34 15.55 12.63 22.41 16.46 12.89 5.33 12.19 18.63
#> 57 58 153 99.1 107 181.2 30 96 36 76 184 42 45
#> 14.46 19.34 21.33 21.19 11.18 16.46 17.43 14.54 21.19 19.22 17.77 12.43 17.42
#> 60.1 77 140.1 133 149.1 76.1 139 96.1 66 24.1 169.1 61.1 5
#> 13.15 7.27 12.68 14.65 8.37 19.22 21.49 14.54 22.13 23.89 22.41 10.12 16.43
#> 149.2 180 96.2 51 36.1 5.1 188.2 123.2 15 42.1 15.1 63 60.2
#> 8.37 14.82 14.54 18.23 21.19 16.43 16.16 13.00 22.68 12.43 22.68 22.77 13.15
#> 86 92.1 167.1 167.2 85.1 39 63.1 86.1 39.1 150 153.1 39.2 81
#> 23.81 22.92 15.55 15.55 16.44 15.59 22.77 23.81 15.59 20.33 21.33 15.59 14.06
#> 167.3 25 175 36.2 149.3 60.3 194 16 51.1 177 13.1 39.3 87
#> 15.55 6.32 21.91 21.19 8.37 13.15 22.40 8.71 18.23 12.53 14.34 15.59 24.00
#> 135 83 122 98 146 162 75 98.1 62 191 75.1 193 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 35 47 95 35.1 156 22 65 146.1 31 54 83.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 193.1 1 95.1 122.1 148 120.1 72 2 173 143 138 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 160 98.2 137 67 151 19 119.1 17 74 151.1 19.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 165 109 146.2 34 163 72.1 3 11 33 185 7 191.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.2 137.1 193.3 163.1 103 9 67.1 148.1 95.2 62.1 19.2 53 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 71 126 118 193.4 34.1 35.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[60]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003385132 0.742736916 0.211632692
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.488626714 0.003365689 0.523806608
#> grade_iii, Cure model
#> 1.144799997
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 25 6.32 1 34 1 0
#> 81 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 66 22.13 1 53 0 0
#> 91 5.33 1 61 0 1
#> 183 9.24 1 67 1 0
#> 41 18.02 1 40 1 0
#> 18 15.21 1 49 1 0
#> 110 17.56 1 65 0 1
#> 43 12.10 1 61 0 1
#> 92 22.92 1 47 0 1
#> 101 9.97 1 10 0 1
#> 36 21.19 1 48 0 1
#> 166 19.98 1 48 0 0
#> 66.1 22.13 1 53 0 0
#> 136 21.83 1 43 0 1
#> 117 17.46 1 26 0 1
#> 158 20.14 1 74 1 0
#> 26 15.77 1 49 0 1
#> 110.1 17.56 1 65 0 1
#> 5 16.43 1 51 0 1
#> 194 22.40 1 38 0 1
#> 18.1 15.21 1 49 1 0
#> 181 16.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 125 15.65 1 67 1 0
#> 128 20.35 1 35 0 1
#> 106 16.67 1 49 1 0
#> 164 23.60 1 76 0 1
#> 124 9.73 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 10 10.53 1 34 0 0
#> 125.1 15.65 1 67 1 0
#> 97 19.14 1 65 0 1
#> 77 7.27 1 67 0 1
#> 168 23.72 1 70 0 0
#> 79 16.23 1 54 1 0
#> 88 18.37 1 47 0 0
#> 171 16.57 1 41 0 1
#> 50 10.02 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 26.1 15.77 1 49 0 1
#> 16 8.71 1 71 0 1
#> 180 14.82 1 37 0 0
#> 113 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 194.1 22.40 1 38 0 1
#> 140 12.68 1 59 1 0
#> 169 22.41 1 46 0 0
#> 101.1 9.97 1 10 0 1
#> 184 17.77 1 38 0 0
#> 128.1 20.35 1 35 0 1
#> 92.1 22.92 1 47 0 1
#> 99 21.19 1 38 0 1
#> 60 13.15 1 38 1 0
#> 92.2 22.92 1 47 0 1
#> 128.2 20.35 1 35 0 1
#> 39 15.59 1 37 0 1
#> 86 23.81 1 58 0 1
#> 183.1 9.24 1 67 1 0
#> 5.1 16.43 1 51 0 1
#> 10.1 10.53 1 34 0 0
#> 63 22.77 1 31 1 0
#> 187.1 9.92 1 39 1 0
#> 166.1 19.98 1 48 0 0
#> 63.1 22.77 1 31 1 0
#> 59 10.16 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 157 15.10 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 183.2 9.24 1 67 1 0
#> 123 13.00 1 44 1 0
#> 150 20.33 1 48 0 0
#> 107 11.18 1 54 1 0
#> 91.1 5.33 1 61 0 1
#> 16.1 8.71 1 71 0 1
#> 107.1 11.18 1 54 1 0
#> 133.1 14.65 1 57 0 0
#> 134 17.81 1 47 1 0
#> 52 10.42 1 52 0 1
#> 26.2 15.77 1 49 0 1
#> 101.2 9.97 1 10 0 1
#> 23 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 145 10.07 1 65 1 0
#> 128.3 20.35 1 35 0 1
#> 89 11.44 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 117.1 17.46 1 26 0 1
#> 37 12.52 1 57 1 0
#> 90 20.94 1 50 0 1
#> 123.1 13.00 1 44 1 0
#> 179 18.63 1 42 0 0
#> 68 20.62 1 44 0 0
#> 32 20.90 1 37 1 0
#> 24 23.89 1 38 0 0
#> 40 18.00 1 28 1 0
#> 199.1 19.81 1 NA 0 1
#> 42 12.43 1 49 0 1
#> 30 17.43 1 78 0 0
#> 192 16.44 1 31 1 0
#> 76.1 19.22 1 54 0 1
#> 197 21.60 1 69 1 0
#> 57 14.46 1 45 0 1
#> 192.1 16.44 1 31 1 0
#> 190 20.81 1 42 1 0
#> 166.2 19.98 1 48 0 0
#> 6 15.64 1 39 0 0
#> 123.2 13.00 1 44 1 0
#> 45 17.42 1 54 0 1
#> 66.2 22.13 1 53 0 0
#> 151 24.00 0 42 0 0
#> 191 24.00 0 60 0 1
#> 33 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 156 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 44.1 24.00 0 56 0 0
#> 120 24.00 0 68 0 1
#> 72 24.00 0 40 0 1
#> 84 24.00 0 39 0 1
#> 135 24.00 0 58 1 0
#> 48 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 126 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 47 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#> 44.2 24.00 0 56 0 0
#> 54 24.00 0 53 1 0
#> 20 24.00 0 46 1 0
#> 94 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 98 24.00 0 34 1 0
#> 87.2 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 1 24.00 0 23 1 0
#> 146 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 151.1 24.00 0 42 0 0
#> 148 24.00 0 61 1 0
#> 196 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 80.1 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 185 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 21 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 119 24.00 0 17 0 0
#> 163.1 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 200 24.00 0 64 0 0
#> 87.3 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 7 24.00 0 37 1 0
#> 54.1 24.00 0 53 1 0
#> 142 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 120.1 24.00 0 68 0 1
#> 146.1 24.00 0 63 1 0
#> 163.2 24.00 0 66 0 0
#> 80.2 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 47.1 24.00 0 38 0 1
#> 131.1 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 94.1 24.00 0 51 0 1
#> 162.1 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 53 24.00 0 32 0 1
#> 103 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 82.1 24.00 0 34 0 0
#> 98.2 24.00 0 34 1 0
#> 11.1 24.00 0 42 0 1
#> 19 24.00 0 57 0 1
#> 83 24.00 0 6 0 0
#> 46 24.00 0 71 0 0
#> 135.1 24.00 0 58 1 0
#> 35.1 24.00 0 51 0 0
#> 47.2 24.00 0 38 0 1
#> 19.1 24.00 0 57 0 1
#> 141 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 172 24.00 0 41 0 0
#> 147.1 24.00 0 76 1 0
#> 138 24.00 0 44 1 0
#> 98.3 24.00 0 34 1 0
#> 118.1 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.489 NA NA NA
#> 2 age, Cure model 0.00337 NA NA NA
#> 3 grade_ii, Cure model 0.524 NA NA NA
#> 4 grade_iii, Cure model 1.14 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00339 NA NA NA
#> 2 grade_ii, Survival model 0.743 NA NA NA
#> 3 grade_iii, Survival model 0.212 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.488627 0.003366 0.523807 1.144800
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 253.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.488626714 0.003365689 0.523806608 1.144799997
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003385132 0.742736916 0.211632692
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.98338224 0.81409530 0.93797704 0.28074907 0.98895343 0.94962514
#> [7] 0.54838584 0.76681967 0.58292197 0.87170154 0.13377958 0.92025244
#> [13] 0.34197869 0.46558928 0.28074907 0.31758481 0.59950077 0.45601887
#> [19] 0.70965489 0.58292197 0.68711168 0.25494570 0.76681967 0.65645742
#> [25] 0.86545823 0.73148775 0.40755561 0.64048894 0.11156367 0.75983974
#> [31] 0.89005702 0.73148775 0.51181251 0.97776786 0.08637843 0.70219500
#> [37] 0.53017031 0.64849381 0.79391700 0.70965489 0.96653594 0.78713881
#> [43] 0.18139327 0.53930961 0.25494570 0.84658363 0.24111896 0.92025244
#> [49] 0.57444166 0.40755561 0.13377958 0.34197869 0.82081698 0.13377958
#> [55] 0.40755561 0.75275963 0.05915132 0.94962514 0.68711168 0.89005702
#> [61] 0.21400459 0.93797704 0.46558928 0.21400459 0.18139327 0.78035283
#> [67] 0.94962514 0.82746300 0.44609441 0.87792172 0.98895343 0.96653594
#> [73] 0.87792172 0.79391700 0.56594414 0.90217216 0.70965489 0.92025244
#> [79] 0.63233313 0.66437885 0.91427365 0.40755561 0.90823088 0.49341839
#> [85] 0.59950077 0.85293036 0.36456065 0.82746300 0.52100376 0.39716100
#> [91] 0.37586722 0.02455227 0.55725561 0.85920477 0.61592096 0.66437885
#> [97] 0.49341839 0.33015412 0.80736684 0.66437885 0.38672253 0.46558928
#> [103] 0.74565275 0.82746300 0.62415313 0.28074907 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 25 81 187 66 91 183 41 18 110 43 92 101 36
#> 6.32 14.06 9.92 22.13 5.33 9.24 18.02 15.21 17.56 12.10 22.92 9.97 21.19
#> 166 66.1 136 117 158 26 110.1 5 194 18.1 181 56 125
#> 19.98 22.13 21.83 17.46 20.14 15.77 17.56 16.43 22.40 15.21 16.46 12.21 15.65
#> 128 106 164 167 10 125.1 97 77 168 79 88 171 133
#> 20.35 16.67 23.60 15.55 10.53 15.65 19.14 7.27 23.72 16.23 18.37 16.57 14.65
#> 26.1 16 180 113 108 194.1 140 169 101.1 184 128.1 92.1 99
#> 15.77 8.71 14.82 22.86 18.29 22.40 12.68 22.41 9.97 17.77 20.35 22.92 21.19
#> 60 92.2 128.2 39 86 183.1 5.1 10.1 63 187.1 166.1 63.1 113.1
#> 13.15 22.92 20.35 15.59 23.81 9.24 16.43 10.53 22.77 9.92 19.98 22.77 22.86
#> 157 183.2 123 150 107 91.1 16.1 107.1 133.1 134 52 26.2 101.2
#> 15.10 9.24 13.00 20.33 11.18 5.33 8.71 11.18 14.65 17.81 10.42 15.77 9.97
#> 23 85 145 128.3 61 76 117.1 37 90 123.1 179 68 32
#> 16.92 16.44 10.07 20.35 10.12 19.22 17.46 12.52 20.94 13.00 18.63 20.62 20.90
#> 24 40 42 30 192 76.1 197 57 192.1 190 166.2 6 123.2
#> 23.89 18.00 12.43 17.43 16.44 19.22 21.60 14.46 16.44 20.81 19.98 15.64 13.00
#> 45 66.2 151 191 33 44 156 80 44.1 120 72 84 135
#> 17.42 22.13 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 173 126 87 47 87.1 44.2 54 20 94 35 84.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.2 118 163 71 72.1 1 146 174 151.1 148 196 62 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 109 28 185 98.1 21 198 119 163.1 131 12 200 87.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 173.1 7 54.1 142 67 120.1 146.1 163.2 80.2 147 47.1 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 94.1 162.1 53 103 82 82.1 98.2 11.1 19 83 46 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 47.2 19.1 141 172 147.1 138 98.3 118.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[61]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006496225 0.335036318 0.328927071
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.00006077 0.01860029 0.01686745
#> grade_iii, Cure model
#> 0.67297590
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 149 8.37 1 33 1 0
#> 155 13.08 1 26 0 0
#> 96 14.54 1 33 0 1
#> 88 18.37 1 47 0 0
#> 24 23.89 1 38 0 0
#> 59 10.16 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 114 13.68 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 100 16.07 1 60 0 0
#> 51 18.23 1 83 0 1
#> 23 16.92 1 61 0 0
#> 125 15.65 1 67 1 0
#> 69 23.23 1 25 0 1
#> 153 21.33 1 55 1 0
#> 79.1 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 66 22.13 1 53 0 0
#> 59.1 10.16 1 NA 1 0
#> 79.2 16.23 1 54 1 0
#> 52 10.42 1 52 0 1
#> 4 17.64 1 NA 0 1
#> 139 21.49 1 63 1 0
#> 117 17.46 1 26 0 1
#> 125.1 15.65 1 67 1 0
#> 36 21.19 1 48 0 1
#> 130 16.47 1 53 0 1
#> 153.1 21.33 1 55 1 0
#> 85 16.44 1 36 0 0
#> 52.1 10.42 1 52 0 1
#> 90 20.94 1 50 0 1
#> 189 10.51 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 154 12.63 1 20 1 0
#> 153.2 21.33 1 55 1 0
#> 167 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 97 19.14 1 65 0 1
#> 127 3.53 1 62 0 1
#> 29 15.45 1 68 1 0
#> 69.1 23.23 1 25 0 1
#> 69.2 23.23 1 25 0 1
#> 18 15.21 1 49 1 0
#> 59.2 10.16 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 97.1 19.14 1 65 0 1
#> 93 10.33 1 52 0 1
#> 10 10.53 1 34 0 0
#> 76 19.22 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 155.1 13.08 1 26 0 0
#> 81 14.06 1 34 0 0
#> 114.1 13.68 1 NA 0 0
#> 123 13.00 1 44 1 0
#> 40 18.00 1 28 1 0
#> 66.1 22.13 1 53 0 0
#> 78.1 23.88 1 43 0 0
#> 153.3 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 177 12.53 1 75 0 0
#> 187 9.92 1 39 1 0
#> 89 11.44 1 NA 0 0
#> 96.1 14.54 1 33 0 1
#> 190 20.81 1 42 1 0
#> 5 16.43 1 51 0 1
#> 197 21.60 1 69 1 0
#> 85.1 16.44 1 36 0 0
#> 149.1 8.37 1 33 1 0
#> 139.1 21.49 1 63 1 0
#> 181 16.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 134 17.81 1 47 1 0
#> 124.1 9.73 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 127.1 3.53 1 62 0 1
#> 23.1 16.92 1 61 0 0
#> 8 18.43 1 32 0 0
#> 108 18.29 1 39 0 1
#> 97.2 19.14 1 65 0 1
#> 91 5.33 1 61 0 1
#> 14 12.89 1 21 0 0
#> 57 14.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 56 12.21 1 60 0 0
#> 96.2 14.54 1 33 0 1
#> 157 15.10 1 47 0 0
#> 153.4 21.33 1 55 1 0
#> 66.2 22.13 1 53 0 0
#> 169 22.41 1 46 0 0
#> 164 23.60 1 76 0 1
#> 171 16.57 1 41 0 1
#> 59.3 10.16 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 39 15.59 1 37 0 1
#> 66.3 22.13 1 53 0 0
#> 140.1 12.68 1 59 1 0
#> 97.3 19.14 1 65 0 1
#> 30 17.43 1 78 0 0
#> 89.2 11.44 1 NA 0 0
#> 114.2 13.68 1 NA 0 0
#> 177.1 12.53 1 75 0 0
#> 79.3 16.23 1 54 1 0
#> 89.3 11.44 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 76.1 19.22 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 189.2 10.51 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 183 9.24 1 67 1 0
#> 90.1 20.94 1 50 0 1
#> 54 24.00 0 53 1 0
#> 143 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 156 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 119 24.00 0 17 0 0
#> 64 24.00 0 43 0 0
#> 119.1 24.00 0 17 0 0
#> 94 24.00 0 51 0 1
#> 142 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 9 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 126 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 64.1 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 116.1 24.00 0 58 0 1
#> 2 24.00 0 9 0 0
#> 185 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 47.1 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 132 24.00 0 55 0 0
#> 161 24.00 0 45 0 0
#> 162 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 71 24.00 0 51 0 0
#> 54.1 24.00 0 53 1 0
#> 162.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 38 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 182 24.00 0 35 0 0
#> 11 24.00 0 42 0 1
#> 28.1 24.00 0 67 1 0
#> 48 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 143.1 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 174.1 24.00 0 49 1 0
#> 146.1 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 116.2 24.00 0 58 0 1
#> 3 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 119.2 24.00 0 17 0 0
#> 87 24.00 0 27 0 0
#> 28.2 24.00 0 67 1 0
#> 185.1 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 115 24.00 0 NA 1 0
#> 176.2 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 142.1 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 146.2 24.00 0 63 1 0
#> 21.1 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 176.3 24.00 0 43 0 1
#> 178.1 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 115.1 24.00 0 NA 1 0
#> 162.2 24.00 0 51 0 0
#> 98.1 24.00 0 34 1 0
#> 132.1 24.00 0 55 0 0
#> 165.1 24.00 0 47 0 0
#> 9.2 24.00 0 31 1 0
#> 174.2 24.00 0 49 1 0
#> 131 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 102 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 75.1 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.00 NA NA NA
#> 2 age, Cure model 0.0186 NA NA NA
#> 3 grade_ii, Cure model 0.0169 NA NA NA
#> 4 grade_iii, Cure model 0.673 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00650 NA NA NA
#> 2 grade_ii, Survival model 0.335 NA NA NA
#> 3 grade_iii, Survival model 0.329 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00006 0.01860 0.01687 0.67298
#>
#> Degrees of Freedom: 177 Total (i.e. Null); 174 Residual
#> Null Deviance: 246.4
#> Residual Deviance: 239.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00006077 0.01860029 0.01686745 0.67297590
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006496225 0.335036318 0.328927071
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.73245222 0.96966496 0.85969659 0.82593736 0.60049690 0.04241218
#> [7] 0.18119454 0.09263698 0.76185692 0.61825351 0.66889833 0.76928230
#> [13] 0.20477601 0.42002538 0.73245222 0.52692636 0.30753834 0.73245222
#> [19] 0.93191759 0.39395351 0.65233697 0.76928230 0.47421904 0.69316605
#> [25] 0.42002538 0.70904910 0.93191759 0.49583066 0.25757894 0.89954536
#> [31] 0.42002538 0.79094993 0.88645321 0.55630012 0.98800125 0.80504704
#> [37] 0.20477601 0.20477601 0.81205436 0.55630012 0.94460672 0.92546775
#> [43] 0.53701359 0.25757894 0.85969659 0.85295065 0.87309699 0.63547016
#> [49] 0.30753834 0.09263698 0.42002538 0.96346885 0.90608714 0.95093232
#> [55] 0.82593736 0.51660696 0.72467535 0.37962951 0.70904910 0.96966496
#> [61] 0.39395351 0.70114631 0.36463310 0.64395310 0.79094993 0.98800125
#> [67] 0.66889833 0.59151985 0.60942630 0.55630012 0.98190343 0.87977881
#> [73] 0.84619150 0.47421904 0.91900679 0.82593736 0.81900636 0.42002538
#> [79] 0.30753834 0.29077852 0.15420873 0.68509656 0.78373912 0.30753834
#> [85] 0.88645321 0.55630012 0.66065189 0.90608714 0.73245222 0.53701359
#> [91] 0.62690987 0.95722440 0.49583066 0.00000000 0.00000000 0.00000000
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 79 149 155 96 88 24 129 78 100 51 23 125 69
#> 16.23 8.37 13.08 14.54 18.37 23.89 23.41 23.88 16.07 18.23 16.92 15.65 23.23
#> 153 79.1 55 66 79.2 52 139 117 125.1 36 130 153.1 85
#> 21.33 16.23 19.34 22.13 16.23 10.42 21.49 17.46 15.65 21.19 16.47 21.33 16.44
#> 52.1 90 63 154 153.2 167 140 97 127 29 69.1 69.2 18
#> 10.42 20.94 22.77 12.63 21.33 15.55 12.68 19.14 3.53 15.45 23.23 23.23 15.21
#> 97.1 93 10 76 63.1 155.1 81 123 40 66.1 78.1 153.3 16
#> 19.14 10.33 10.53 19.22 22.77 13.08 14.06 13.00 18.00 22.13 23.88 21.33 8.71
#> 177 187 96.1 190 5 197 85.1 149.1 139.1 181 175 134 167.1
#> 12.53 9.92 14.54 20.81 16.43 21.60 16.44 8.37 21.49 16.46 21.91 17.81 15.55
#> 127.1 23.1 8 108 97.2 91 14 57 99 56 96.2 157 153.4
#> 3.53 16.92 18.43 18.29 19.14 5.33 12.89 14.46 21.19 12.21 14.54 15.10 21.33
#> 66.2 169 164 171 39 66.3 140.1 97.3 30 177.1 79.3 76.1 41
#> 22.13 22.41 23.60 16.57 15.59 22.13 12.68 19.14 17.43 12.53 16.23 19.22 18.02
#> 183 90.1 54 143 186 98 156 178 198 119 64 119.1 94
#> 9.24 20.94 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 47 19 7 144 9 116 126 120 64.1 151 116.1 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 120.1 176 47.1 186.1 118 146 20 132 161 162 151.1 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 162.1 174 38 28 182 11 28.1 48 148 143.1 9.1 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 174.1 146.1 44 116.2 3 84 119.2 87 28.2 185.1 20.1 176.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 142.1 21 146.2 21.1 165 121 72 176.3 178.1 53 162.2 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 165.1 9.2 174.2 131 102 46 75.1 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[62]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0162257 0.8975902 0.4802673
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.195258849 -0.004371631 -0.406948855
#> grade_iii, Cure model
#> 0.709023569
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 25 6.32 1 34 1 0
#> 108 18.29 1 39 0 1
#> 136 21.83 1 43 0 1
#> 25.1 6.32 1 34 1 0
#> 111 17.45 1 47 0 1
#> 26 15.77 1 49 0 1
#> 90 20.94 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 150 20.33 1 48 0 0
#> 113 22.86 1 34 0 0
#> 157 15.10 1 47 0 0
#> 128 20.35 1 35 0 1
#> 188 16.16 1 46 0 1
#> 26.1 15.77 1 49 0 1
#> 171 16.57 1 41 0 1
#> 199 19.81 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 149 8.37 1 33 1 0
#> 99 21.19 1 38 0 1
#> 164 23.60 1 76 0 1
#> 66.1 22.13 1 53 0 0
#> 24 23.89 1 38 0 0
#> 136.1 21.83 1 43 0 1
#> 99.1 21.19 1 38 0 1
#> 159 10.55 1 50 0 1
#> 110 17.56 1 65 0 1
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 177 12.53 1 75 0 0
#> 63 22.77 1 31 1 0
#> 108.1 18.29 1 39 0 1
#> 153 21.33 1 55 1 0
#> 24.1 23.89 1 38 0 0
#> 36 21.19 1 48 0 1
#> 59.1 10.16 1 NA 1 0
#> 164.1 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 164.2 23.60 1 76 0 1
#> 166 19.98 1 48 0 0
#> 164.3 23.60 1 76 0 1
#> 107 11.18 1 54 1 0
#> 171.1 16.57 1 41 0 1
#> 58 19.34 1 39 0 0
#> 57 14.46 1 45 0 1
#> 128.1 20.35 1 35 0 1
#> 14 12.89 1 21 0 0
#> 145 10.07 1 65 1 0
#> 150.1 20.33 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 18 15.21 1 49 1 0
#> 130 16.47 1 53 0 1
#> 24.2 23.89 1 38 0 0
#> 123 13.00 1 44 1 0
#> 189 10.51 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 199.1 19.81 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 76 19.22 1 54 0 1
#> 145.1 10.07 1 65 1 0
#> 136.2 21.83 1 43 0 1
#> 133 14.65 1 57 0 0
#> 16 8.71 1 71 0 1
#> 14.1 12.89 1 21 0 0
#> 154 12.63 1 20 1 0
#> 110.1 17.56 1 65 0 1
#> 93 10.33 1 52 0 1
#> 199.2 19.81 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 108.2 18.29 1 39 0 1
#> 57.1 14.46 1 45 0 1
#> 136.3 21.83 1 43 0 1
#> 18.1 15.21 1 49 1 0
#> 129 23.41 1 53 1 0
#> 175 21.91 1 43 0 0
#> 114.1 13.68 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 105 19.75 1 60 0 0
#> 110.2 17.56 1 65 0 1
#> 36.1 21.19 1 48 0 1
#> 66.2 22.13 1 53 0 0
#> 188.1 16.16 1 46 0 1
#> 66.3 22.13 1 53 0 0
#> 69 23.23 1 25 0 1
#> 101.1 9.97 1 10 0 1
#> 187.1 9.92 1 39 1 0
#> 52 10.42 1 52 0 1
#> 153.1 21.33 1 55 1 0
#> 189.1 10.51 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 179 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 57.2 14.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 187.2 9.92 1 39 1 0
#> 5 16.43 1 51 0 1
#> 114.2 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 110.3 17.56 1 65 0 1
#> 100 16.07 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 181 16.46 1 45 0 1
#> 157.1 15.10 1 47 0 0
#> 125 15.65 1 67 1 0
#> 192 16.44 1 31 1 0
#> 150.2 20.33 1 48 0 0
#> 153.2 21.33 1 55 1 0
#> 181.1 16.46 1 45 0 1
#> 96 14.54 1 33 0 1
#> 5.1 16.43 1 51 0 1
#> 68.1 20.62 1 44 0 0
#> 137 24.00 0 45 1 0
#> 19 24.00 0 57 0 1
#> 161 24.00 0 45 0 0
#> 94 24.00 0 51 0 1
#> 196 24.00 0 19 0 0
#> 138 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 47 24.00 0 38 0 1
#> 17 24.00 0 38 0 1
#> 102 24.00 0 49 0 0
#> 71 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 148 24.00 0 61 1 0
#> 102.1 24.00 0 49 0 0
#> 122 24.00 0 66 0 0
#> 122.1 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 27 24.00 0 63 1 0
#> 173 24.00 0 19 0 1
#> 62 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 143 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 186.1 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 104 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 144 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 200 24.00 0 64 0 0
#> 191.1 24.00 0 60 0 1
#> 19.2 24.00 0 57 0 1
#> 2.1 24.00 0 9 0 0
#> 83 24.00 0 6 0 0
#> 62.1 24.00 0 71 0 0
#> 104.1 24.00 0 50 1 0
#> 104.2 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 132.1 24.00 0 55 0 0
#> 161.1 24.00 0 45 0 0
#> 20 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 178 24.00 0 52 1 0
#> 196.1 24.00 0 19 0 0
#> 27.1 24.00 0 63 1 0
#> 19.3 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 75.2 24.00 0 21 1 0
#> 146.1 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 17.1 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 200.1 24.00 0 64 0 0
#> 186.2 24.00 0 45 1 0
#> 62.2 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 148.1 24.00 0 61 1 0
#> 11.1 24.00 0 42 0 1
#> 83.1 24.00 0 6 0 0
#> 62.3 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 126 24.00 0 48 0 0
#> 109 24.00 0 48 0 0
#> 116.1 24.00 0 58 0 1
#> 53.1 24.00 0 32 0 1
#> 148.2 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 64 24.00 0 43 0 0
#> 112.1 24.00 0 61 0 0
#> 28.1 24.00 0 67 1 0
#> 174 24.00 0 49 1 0
#> 178.1 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 120.1 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.195 NA NA NA
#> 2 age, Cure model -0.00437 NA NA NA
#> 3 grade_ii, Cure model -0.407 NA NA NA
#> 4 grade_iii, Cure model 0.709 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0162 NA NA NA
#> 2 grade_ii, Survival model 0.898 NA NA NA
#> 3 grade_iii, Survival model 0.480 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.195259 -0.004372 -0.406949 0.709024
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262.4
#> Residual Deviance: 252.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.195258849 -0.004371631 -0.406948855 0.709023569
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0162257 0.8975902 0.4802673
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.974759782 0.283632565 0.081075909 0.974759782 0.375863101 0.523483936
#> [7] 0.159532156 0.273638906 0.200223315 0.032590157 0.594783108 0.183794072
#> [13] 0.488638860 0.523483936 0.398127816 0.043625914 0.961918601 0.130390034
#> [19] 0.006987461 0.043625914 0.001095863 0.081075909 0.130390034 0.781426229
#> [25] 0.333756469 0.794204953 0.885203029 0.743314410 0.038299072 0.283632565
#> [31] 0.108833420 0.001095863 0.130390034 0.006987461 0.386943096 0.006987461
#> [37] 0.226039836 0.006987461 0.768706128 0.398127816 0.244570647 0.643650718
#> [43] 0.183794072 0.705647624 0.859093665 0.200223315 0.794204953 0.571135479
#> [49] 0.420391599 0.001095863 0.693089070 0.312995658 0.911027297 0.254121372
#> [55] 0.859093665 0.081075909 0.618943312 0.949002177 0.705647624 0.730797482
#> [61] 0.333756469 0.832919500 0.167488009 0.283632565 0.643650718 0.081075909
#> [67] 0.571135479 0.021886481 0.066851161 0.845996595 0.235191684 0.333756469
#> [73] 0.130390034 0.043625914 0.488638860 0.043625914 0.027277152 0.885203029
#> [79] 0.911027297 0.819904677 0.108833420 0.755981478 0.263790941 0.323299368
#> [85] 0.643650718 0.559132520 0.911027297 0.465859765 0.680484480 0.333756469
#> [91] 0.511668953 0.066851161 0.431771421 0.594783108 0.547132402 0.454492682
#> [97] 0.200223315 0.108833420 0.431771421 0.631290522 0.465859765 0.167488009
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 25 108 136 25.1 111 26 90 8 150 113 157 128 188
#> 6.32 18.29 21.83 6.32 17.45 15.77 20.94 18.43 20.33 22.86 15.10 20.35 16.16
#> 26.1 171 66 149 99 164 66.1 24 136.1 99.1 159 110 10
#> 15.77 16.57 22.13 8.37 21.19 23.60 22.13 23.89 21.83 21.19 10.55 17.56 10.53
#> 101 177 63 108.1 153 24.1 36 164.1 45 164.2 166 164.3 107
#> 9.97 12.53 22.77 18.29 21.33 23.89 21.19 23.60 17.42 23.60 19.98 23.60 11.18
#> 171.1 58 57 128.1 14 145 150.1 10.1 18 130 24.2 123 51
#> 16.57 19.34 14.46 20.35 12.89 10.07 20.33 10.53 15.21 16.47 23.89 13.00 18.23
#> 187 76 145.1 136.2 133 16 14.1 154 110.1 93 68 108.2 57.1
#> 9.92 19.22 10.07 21.83 14.65 8.71 12.89 12.63 17.56 10.33 20.62 18.29 14.46
#> 136.3 18.1 129 175 61 105 110.2 36.1 66.2 188.1 66.3 69 101.1
#> 21.83 15.21 23.41 21.91 10.12 19.75 17.56 21.19 22.13 16.16 22.13 23.23 9.97
#> 187.1 52 153.1 42 179 184 57.2 167 187.2 5 81 110.3 100
#> 9.92 10.42 21.33 12.43 18.63 17.77 14.46 15.55 9.92 16.43 14.06 17.56 16.07
#> 175.1 181 157.1 125 192 150.2 153.2 181.1 96 5.1 68.1 137 19
#> 21.91 16.46 15.10 15.65 16.44 20.33 21.33 16.46 14.54 16.43 20.62 24.00 24.00
#> 161 94 196 138 19.1 47 17 102 71 28 148 102.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 75 87 27 173 62 186 112 143 116 84 186.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 191 144 82 2 200 191.1 19.2 2.1 83 62.1 104.1 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 146 95 132.1 161.1 20 75.1 178 196.1 27.1 19.3 72 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.2 146.1 22 193 17.1 121 141 65 200.1 186.2 62.2 11 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 83.1 62.3 119 126 109 116.1 53.1 148.2 152 9 54 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 28.1 174 178.1 35 98 120.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[63]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009103739 0.761502188 0.585140336
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.71148761 0.01263085 -0.11096987
#> grade_iii, Cure model
#> 0.95058375
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 158 20.14 1 74 1 0
#> 41 18.02 1 40 1 0
#> 29 15.45 1 68 1 0
#> 78 23.88 1 43 0 0
#> 129 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 52 10.42 1 52 0 1
#> 107 11.18 1 54 1 0
#> 117 17.46 1 26 0 1
#> 113 22.86 1 34 0 0
#> 145 10.07 1 65 1 0
#> 6 15.64 1 39 0 0
#> 10 10.53 1 34 0 0
#> 158.1 20.14 1 74 1 0
#> 108 18.29 1 39 0 1
#> 100 16.07 1 60 0 0
#> 183 9.24 1 67 1 0
#> 25 6.32 1 34 1 0
#> 136 21.83 1 43 0 1
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 128 20.35 1 35 0 1
#> 51 18.23 1 83 0 1
#> 70 7.38 1 30 1 0
#> 61.1 10.12 1 36 0 1
#> 91 5.33 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 127 3.53 1 62 0 1
#> 130 16.47 1 53 0 1
#> 8 18.43 1 32 0 0
#> 43 12.10 1 61 0 1
#> 183.1 9.24 1 67 1 0
#> 14 12.89 1 21 0 0
#> 155 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 13 14.34 1 54 0 1
#> 77 7.27 1 67 0 1
#> 134 17.81 1 47 1 0
#> 127.1 3.53 1 62 0 1
#> 107.1 11.18 1 54 1 0
#> 194 22.40 1 38 0 1
#> 195 11.76 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 24 23.89 1 38 0 0
#> 189.1 10.51 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 49 12.19 1 48 1 0
#> 155.1 13.08 1 26 0 0
#> 85 16.44 1 36 0 0
#> 43.1 12.10 1 61 0 1
#> 6.1 15.64 1 39 0 0
#> 15 22.68 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 175 21.91 1 43 0 0
#> 101 9.97 1 10 0 1
#> 89 11.44 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 108.2 18.29 1 39 0 1
#> 14.1 12.89 1 21 0 0
#> 164 23.60 1 76 0 1
#> 127.2 3.53 1 62 0 1
#> 164.1 23.60 1 76 0 1
#> 13.1 14.34 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 92 22.92 1 47 0 1
#> 52.1 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 50 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 125 15.65 1 67 1 0
#> 29.1 15.45 1 68 1 0
#> 26 15.77 1 49 0 1
#> 136.1 21.83 1 43 0 1
#> 24.1 23.89 1 38 0 0
#> 97 19.14 1 65 0 1
#> 100.1 16.07 1 60 0 0
#> 105 19.75 1 60 0 0
#> 61.2 10.12 1 36 0 1
#> 78.1 23.88 1 43 0 0
#> 18.1 15.21 1 49 1 0
#> 57 14.46 1 45 0 1
#> 117.1 17.46 1 26 0 1
#> 177 12.53 1 75 0 0
#> 25.1 6.32 1 34 1 0
#> 55 19.34 1 69 0 1
#> 190 20.81 1 42 1 0
#> 93 10.33 1 52 0 1
#> 184 17.77 1 38 0 0
#> 154 12.63 1 20 1 0
#> 50.1 10.02 1 NA 1 0
#> 43.2 12.10 1 61 0 1
#> 57.1 14.46 1 45 0 1
#> 60 13.15 1 38 1 0
#> 42 12.43 1 49 0 1
#> 99 21.19 1 38 0 1
#> 61.3 10.12 1 36 0 1
#> 114.1 13.68 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 197 21.60 1 69 1 0
#> 66 22.13 1 53 0 0
#> 45 17.42 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 197.1 21.60 1 69 1 0
#> 125.1 15.65 1 67 1 0
#> 145.1 10.07 1 65 1 0
#> 41.1 18.02 1 40 1 0
#> 184.1 17.77 1 38 0 0
#> 184.2 17.77 1 38 0 0
#> 110 17.56 1 65 0 1
#> 2 24.00 0 9 0 0
#> 191 24.00 0 60 0 1
#> 196 24.00 0 19 0 0
#> 191.1 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 138.1 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 141 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 21 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 182.1 24.00 0 35 0 0
#> 196.1 24.00 0 19 0 0
#> 44 24.00 0 56 0 0
#> 178 24.00 0 52 1 0
#> 138.2 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 193 24.00 0 45 0 1
#> 11 24.00 0 42 0 1
#> 98 24.00 0 34 1 0
#> 103 24.00 0 56 1 0
#> 176 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 138.3 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 46 24.00 0 71 0 0
#> 65.1 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 196.2 24.00 0 19 0 0
#> 163.1 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 34 24.00 0 36 0 0
#> 148.1 24.00 0 61 1 0
#> 22 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 19.1 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 94 24.00 0 51 0 1
#> 146.1 24.00 0 63 1 0
#> 3.1 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 138.4 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 152.1 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 87.1 24.00 0 27 0 0
#> 35.1 24.00 0 51 0 0
#> 178.2 24.00 0 52 1 0
#> 35.2 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 54 24.00 0 53 1 0
#> 193.1 24.00 0 45 0 1
#> 162 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 22.1 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 80.1 24.00 0 41 0 0
#> 148.2 24.00 0 61 1 0
#> 200 24.00 0 64 0 0
#> 87.2 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 98.1 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 75.1 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 122 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 138.5 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 156.2 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.711 NA NA NA
#> 2 age, Cure model 0.0126 NA NA NA
#> 3 grade_ii, Cure model -0.111 NA NA NA
#> 4 grade_iii, Cure model 0.951 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00910 NA NA NA
#> 2 grade_ii, Survival model 0.762 NA NA NA
#> 3 grade_iii, Survival model 0.585 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71149 0.01263 -0.11097 0.95058
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 252.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.71148761 0.01263085 -0.11096987 0.95058375
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009103739 0.761502188 0.585140336
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.245471799 0.364201693 0.593286031 0.018611131 0.071059373 0.847200637
#> [7] 0.819314289 0.791397413 0.440846252 0.100624640 0.883417446 0.574084910
#> [13] 0.809953684 0.245471799 0.324979246 0.526265790 0.910746990 0.946833351
#> [19] 0.154212784 0.507389892 0.507389892 0.235626163 0.354152735 0.928800255
#> [25] 0.847200637 0.964590353 0.459714622 0.973507601 0.488256152 0.304541844
#> [31] 0.763525570 0.910746990 0.706839369 0.688018540 0.038340262 0.659752617
#> [37] 0.937815741 0.393127169 0.973507601 0.791397413 0.121772951 0.612392546
#> [43] 0.004528719 0.195466094 0.754109065 0.688018540 0.497797331 0.763525570
#> [49] 0.574084910 0.111020329 0.324979246 0.143107967 0.901645512 0.383510052
#> [55] 0.478694783 0.324979246 0.706839369 0.049792684 0.973507601 0.049792684
#> [61] 0.659752617 0.071059373 0.090507850 0.819314289 0.631280594 0.215473207
#> [67] 0.555073860 0.593286031 0.545431040 0.154212784 0.004528719 0.294465887
#> [73] 0.526265790 0.264630759 0.847200637 0.018611131 0.612392546 0.640854763
#> [79] 0.440846252 0.735167501 0.946833351 0.284392232 0.225653344 0.837878710
#> [85] 0.402652027 0.725747834 0.763525570 0.640854763 0.678597583 0.744647267
#> [91] 0.195466094 0.847200637 0.314702784 0.175011195 0.132275711 0.469214109
#> [97] 0.264630759 0.175011195 0.555073860 0.883417446 0.364201693 0.402652027
#> [103] 0.402652027 0.431133790 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 158 41 29 78 129 61 52 107 117 113 145 6 10
#> 20.14 18.02 15.45 23.88 23.41 10.12 10.42 11.18 17.46 22.86 10.07 15.64 10.53
#> 158.1 108 100 183 25 136 188 188.1 128 51 70 61.1 91
#> 20.14 18.29 16.07 9.24 6.32 21.83 16.16 16.16 20.35 18.23 7.38 10.12 5.33
#> 111 127 130 8 43 183.1 14 155 86 13 77 134 127.1
#> 17.45 3.53 16.47 18.43 12.10 9.24 12.89 13.08 23.81 14.34 7.27 17.81 3.53
#> 107.1 194 18 24 36 49 155.1 85 43.1 6.1 15 108.1 175
#> 11.18 22.40 15.21 23.89 21.19 12.19 13.08 16.44 12.10 15.64 22.68 18.29 21.91
#> 101 40 23 108.2 14.1 164 127.2 164.1 13.1 129.1 92 52.1 133
#> 9.97 18.00 16.92 18.29 12.89 23.60 3.53 23.60 14.34 23.41 22.92 10.42 14.65
#> 90 125 29.1 26 136.1 24.1 97 100.1 105 61.2 78.1 18.1 57
#> 20.94 15.65 15.45 15.77 21.83 23.89 19.14 16.07 19.75 10.12 23.88 15.21 14.46
#> 117.1 177 25.1 55 190 93 184 154 43.2 57.1 60 42 99
#> 17.46 12.53 6.32 19.34 20.81 10.33 17.77 12.63 12.10 14.46 13.15 12.43 21.19
#> 61.3 88 197 66 45 105.1 197.1 125.1 145.1 41.1 184.1 184.2 110
#> 10.12 18.37 21.60 22.13 17.42 19.75 21.60 15.65 10.07 18.02 17.77 17.77 17.56
#> 2 191 196 191.1 138 152 31 182 161 19 138.1 163 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 3 104 65 17 112 120 146 148 21 126 182.1 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 178 138.2 112.1 193 11 98 103 176 9 138.3 147 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 35 196.2 163.1 116 34 148.1 22 198 19.1 53 94 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 75 87 138.4 131 20 152.1 178.1 67 87.1 35.1 178.2 35.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 54 193.1 162 119 22.1 176.1 80 33 80.1 148.2 200 87.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 98.1 174 75.1 173 122 131.1 138.5 156.1 156.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[64]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01540235 0.42723626 -0.02119489
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.16210339 0.01838523 0.30348012
#> grade_iii, Cure model
#> 1.05095221
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 192 16.44 1 31 1 0
#> 192.1 16.44 1 31 1 0
#> 139 21.49 1 63 1 0
#> 66 22.13 1 53 0 0
#> 171 16.57 1 41 0 1
#> 14 12.89 1 21 0 0
#> 15 22.68 1 48 0 0
#> 93 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 57 14.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 78 23.88 1 43 0 0
#> 179 18.63 1 42 0 0
#> 136 21.83 1 43 0 1
#> 30 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 76 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 167 15.55 1 56 1 0
#> 85 16.44 1 36 0 0
#> 168 23.72 1 70 0 0
#> 16.1 8.71 1 71 0 1
#> 181 16.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 86 23.81 1 58 0 1
#> 125 15.65 1 67 1 0
#> 171.1 16.57 1 41 0 1
#> 129 23.41 1 53 1 0
#> 36 21.19 1 48 0 1
#> 14.1 12.89 1 21 0 0
#> 111 17.45 1 47 0 1
#> 37 12.52 1 57 1 0
#> 195 11.76 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 133 14.65 1 57 0 0
#> 99 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 139.1 21.49 1 63 1 0
#> 154 12.63 1 20 1 0
#> 16.2 8.71 1 71 0 1
#> 133.1 14.65 1 57 0 0
#> 157 15.10 1 47 0 0
#> 18 15.21 1 49 1 0
#> 153 21.33 1 55 1 0
#> 181.1 16.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 6 15.64 1 39 0 0
#> 70 7.38 1 30 1 0
#> 192.2 16.44 1 31 1 0
#> 194.1 22.40 1 38 0 1
#> 61 10.12 1 36 0 1
#> 145 10.07 1 65 1 0
#> 195.1 11.76 1 NA 1 0
#> 167.1 15.55 1 56 1 0
#> 5 16.43 1 51 0 1
#> 183 9.24 1 67 1 0
#> 166 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 167.2 15.55 1 56 1 0
#> 180 14.82 1 37 0 0
#> 60 13.15 1 38 1 0
#> 70.1 7.38 1 30 1 0
#> 133.2 14.65 1 57 0 0
#> 117 17.46 1 26 0 1
#> 15.1 22.68 1 48 0 0
#> 127.1 3.53 1 62 0 1
#> 96 14.54 1 33 0 1
#> 86.1 23.81 1 58 0 1
#> 40 18.00 1 28 1 0
#> 195.2 11.76 1 NA 1 0
#> 99.1 21.19 1 38 0 1
#> 158 20.14 1 74 1 0
#> 30.1 17.43 1 78 0 0
#> 97 19.14 1 65 0 1
#> 29 15.45 1 68 1 0
#> 60.1 13.15 1 38 1 0
#> 57.1 14.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 10.1 10.53 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 149 8.37 1 33 1 0
#> 93.1 10.33 1 52 0 1
#> 117.1 17.46 1 26 0 1
#> 5.1 16.43 1 51 0 1
#> 139.2 21.49 1 63 1 0
#> 110 17.56 1 65 0 1
#> 76.1 19.22 1 54 0 1
#> 92.1 22.92 1 47 0 1
#> 192.3 16.44 1 31 1 0
#> 136.1 21.83 1 43 0 1
#> 26.1 15.77 1 49 0 1
#> 110.1 17.56 1 65 0 1
#> 89 11.44 1 NA 0 0
#> 158.1 20.14 1 74 1 0
#> 39 15.59 1 37 0 1
#> 90 20.94 1 50 0 1
#> 167.3 15.55 1 56 1 0
#> 55 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 61.1 10.12 1 36 0 1
#> 164.1 23.60 1 76 0 1
#> 181.2 16.46 1 45 0 1
#> 192.4 16.44 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 43 12.10 1 61 0 1
#> 70.2 7.38 1 30 1 0
#> 197 21.60 1 69 1 0
#> 32 20.90 1 37 1 0
#> 152 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 148 24.00 0 61 1 0
#> 121 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 147 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 160.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 135 24.00 0 58 1 0
#> 116 24.00 0 58 0 1
#> 182 24.00 0 35 0 0
#> 73 24.00 0 NA 0 1
#> 116.1 24.00 0 58 0 1
#> 156 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 20 24.00 0 46 1 0
#> 20.1 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 178 24.00 0 52 1 0
#> 163 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 152.1 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 198 24.00 0 66 0 1
#> 2 24.00 0 9 0 0
#> 20.2 24.00 0 46 1 0
#> 131 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 163.1 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 75.2 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 11 24.00 0 42 0 1
#> 98.1 24.00 0 34 1 0
#> 22 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 84 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 144.1 24.00 0 28 0 1
#> 22.1 24.00 0 52 1 0
#> 34.1 24.00 0 36 0 0
#> 152.2 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 141 24.00 0 44 1 0
#> 163.2 24.00 0 66 0 0
#> 186.1 24.00 0 45 1 0
#> 146 24.00 0 63 1 0
#> 198.1 24.00 0 66 0 1
#> 200 24.00 0 64 0 0
#> 126 24.00 0 48 0 0
#> 142.1 24.00 0 53 0 0
#> 7.1 24.00 0 37 1 0
#> 17 24.00 0 38 0 1
#> 38.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 17.1 24.00 0 38 0 1
#> 46.1 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 83 24.00 0 6 0 0
#> 102 24.00 0 49 0 0
#> 53 24.00 0 32 0 1
#> 112 24.00 0 61 0 0
#> 176 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 161 24.00 0 45 0 0
#> 102.1 24.00 0 49 0 0
#> 2.1 24.00 0 9 0 0
#> 19.2 24.00 0 57 0 1
#> 119.1 24.00 0 17 0 0
#> 122 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.16 NA NA NA
#> 2 age, Cure model 0.0184 NA NA NA
#> 3 grade_ii, Cure model 0.303 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0154 NA NA NA
#> 2 grade_ii, Survival model 0.427 NA NA NA
#> 3 grade_iii, Survival model -0.0212 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16210 0.01839 0.30348 1.05095
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 252.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.16210339 0.01838523 0.30348012 1.05095221
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01540235 0.42723626 -0.02119489
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 6.882207e-01 2.672289e-01 2.672289e-01 3.587923e-02 2.161615e-02
#> [6] 2.183076e-01 6.318404e-01 1.110908e-02 7.466123e-01 8.541189e-01
#> [11] 5.631196e-01 3.571543e-01 2.753402e-05 1.351956e-01 2.491273e-02
#> [16] 1.911030e-01 1.596757e-02 1.139323e-01 2.089503e-01 3.462416e-01
#> [21] 4.141096e-01 2.672289e-01 8.740967e-04 8.541189e-01 2.373888e-01
#> [26] 9.668496e-01 1.914586e-04 3.793678e-01 2.183076e-01 3.865017e-03
#> [31] 5.254566e-02 6.318404e-01 1.825344e-01 6.739877e-01 1.598123e-03
#> [36] 5.108787e-01 5.254566e-02 7.163211e-03 3.587923e-02 6.598628e-01
#> [41] 8.541189e-01 5.108787e-01 4.855976e-01 4.731921e-01 4.797336e-02
#> [46] 2.373888e-01 8.227753e-01 3.907962e-01 9.185753e-01 2.672289e-01
#> [51] 1.596757e-02 7.766561e-01 8.072173e-01 4.141096e-01 3.249797e-01
#> [56] 8.383806e-01 8.864940e-02 5.902481e-01 4.141096e-01 4.981685e-01
#> [61] 6.041575e-01 9.185753e-01 5.108787e-01 1.661928e-01 1.110908e-02
#> [66] 9.668496e-01 5.497215e-01 1.914586e-04 1.427903e-01 5.254566e-02
#> [71] 7.747471e-02 1.911030e-01 1.277990e-01 4.608769e-01 6.041575e-01
#> [76] 5.631196e-01 7.172313e-01 7.172313e-01 5.429422e-03 9.022237e-01
#> [81] 7.466123e-01 1.661928e-01 3.249797e-01 3.587923e-02 1.503867e-01
#> [86] 1.139323e-01 7.163211e-03 2.672289e-01 2.491273e-02 3.571543e-01
#> [91] 1.503867e-01 7.747471e-02 4.023776e-01 6.674426e-02 4.141096e-01
#> [96] 1.072563e-01 9.462850e-02 7.766561e-01 1.598123e-03 2.373888e-01
#> [101] 2.672289e-01 1.008445e-01 7.026336e-01 9.185753e-01 3.193402e-02
#> [106] 7.208286e-02 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 56 192 192.1 139 66 171 14 15 93 16 57 26 78
#> 12.21 16.44 16.44 21.49 22.13 16.57 12.89 22.68 10.33 8.71 14.46 15.77 23.88
#> 179 136 30 194 76 45 79 167 85 168 16.1 181 127
#> 18.63 21.83 17.43 22.40 19.22 17.42 16.23 15.55 16.44 23.72 8.71 16.46 3.53
#> 86 125 171.1 129 36 14.1 111 37 164 133 99 92 139.1
#> 23.81 15.65 16.57 23.41 21.19 12.89 17.45 12.52 23.60 14.65 21.19 22.92 21.49
#> 154 16.2 133.1 157 18 153 181.1 101 6 70 192.2 194.1 61
#> 12.63 8.71 14.65 15.10 15.21 21.33 16.46 9.97 15.64 7.38 16.44 22.40 10.12
#> 145 167.1 5 183 166 13 167.2 180 60 70.1 133.2 117 15.1
#> 10.07 15.55 16.43 9.24 19.98 14.34 15.55 14.82 13.15 7.38 14.65 17.46 22.68
#> 127.1 96 86.1 40 99.1 158 30.1 97 29 60.1 57.1 10 10.1
#> 3.53 14.54 23.81 18.00 21.19 20.14 17.43 19.14 15.45 13.15 14.46 10.53 10.53
#> 69 149 93.1 117.1 5.1 139.2 110 76.1 92.1 192.3 136.1 26.1 110.1
#> 23.23 8.37 10.33 17.46 16.43 21.49 17.56 19.22 22.92 16.44 21.83 15.77 17.56
#> 158.1 39 90 167.3 55 105 61.1 164.1 181.2 192.4 170 43 70.2
#> 20.14 15.59 20.94 15.55 19.34 19.75 10.12 23.60 16.46 16.44 19.54 12.10 7.38
#> 197 32 152 34 148 121 19 147 65 185 38 151 160
#> 21.60 20.90 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 160.1 80 75 135 116 182 116.1 156 35 173 20 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 178 163 19.1 142 152.1 119 144 198 2 20.2 131 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 7 75.2 87 46 48 193 11 98.1 22 120 186 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 74 144.1 22.1 34.1 152.2 47 72 141 163.2 186.1 146 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 126 142.1 7.1 17 38.1 71 67 17.1 46.1 103 83 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 112 176 138 147.1 161 102.1 2.1 19.2 119.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[65]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007048959 0.671690411 0.625055912
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.110211978 -0.006653756 0.334313916
#> grade_iii, Cure model
#> 0.990500426
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 113 22.86 1 34 0 0
#> 91 5.33 1 61 0 1
#> 108 18.29 1 39 0 1
#> 51 18.23 1 83 0 1
#> 107 11.18 1 54 1 0
#> 16 8.71 1 71 0 1
#> 113.1 22.86 1 34 0 0
#> 187 9.92 1 39 1 0
#> 55 19.34 1 69 0 1
#> 140 12.68 1 59 1 0
#> 127 3.53 1 62 0 1
#> 69 23.23 1 25 0 1
#> 108.1 18.29 1 39 0 1
#> 85 16.44 1 36 0 0
#> 159 10.55 1 50 0 1
#> 93 10.33 1 52 0 1
#> 92 22.92 1 47 0 1
#> 8 18.43 1 32 0 0
#> 129 23.41 1 53 1 0
#> 124 9.73 1 NA 1 0
#> 108.2 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 99 21.19 1 38 0 1
#> 18 15.21 1 49 1 0
#> 167 15.55 1 56 1 0
#> 5 16.43 1 51 0 1
#> 29 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 59 10.16 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 189 10.51 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 68 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 97 19.14 1 65 0 1
#> 13 14.34 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 49 12.19 1 48 1 0
#> 25 6.32 1 34 1 0
#> 150 20.33 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 14 12.89 1 21 0 0
#> 86 23.81 1 58 0 1
#> 106 16.67 1 49 1 0
#> 114 13.68 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 89.1 11.44 1 NA 0 0
#> 129.1 23.41 1 53 1 0
#> 41 18.02 1 40 1 0
#> 123 13.00 1 44 1 0
#> 49.1 12.19 1 48 1 0
#> 51.1 18.23 1 83 0 1
#> 89.2 11.44 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 10 10.53 1 34 0 0
#> 37 12.52 1 57 1 0
#> 171 16.57 1 41 0 1
#> 169 22.41 1 46 0 0
#> 57 14.46 1 45 0 1
#> 85.1 16.44 1 36 0 0
#> 15 22.68 1 48 0 0
#> 8.1 18.43 1 32 0 0
#> 24.1 23.89 1 38 0 0
#> 194 22.40 1 38 0 1
#> 177 12.53 1 75 0 0
#> 199 19.81 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 52 10.42 1 52 0 1
#> 86.1 23.81 1 58 0 1
#> 69.1 23.23 1 25 0 1
#> 14.1 12.89 1 21 0 0
#> 184 17.77 1 38 0 0
#> 40 18.00 1 28 1 0
#> 43 12.10 1 61 0 1
#> 168 23.72 1 70 0 0
#> 43.1 12.10 1 61 0 1
#> 49.2 12.19 1 48 1 0
#> 78.1 23.88 1 43 0 0
#> 29.1 15.45 1 68 1 0
#> 68.1 20.62 1 44 0 0
#> 180 14.82 1 37 0 0
#> 13.1 14.34 1 54 0 1
#> 157 15.10 1 47 0 0
#> 45 17.42 1 54 0 1
#> 52.1 10.42 1 52 0 1
#> 155 13.08 1 26 0 0
#> 189.1 10.51 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 171.1 16.57 1 41 0 1
#> 41.1 18.02 1 40 1 0
#> 149 8.37 1 33 1 0
#> 78.2 23.88 1 43 0 0
#> 111 17.45 1 47 0 1
#> 60 13.15 1 38 1 0
#> 63 22.77 1 31 1 0
#> 52.2 10.42 1 52 0 1
#> 29.2 15.45 1 68 1 0
#> 50 10.02 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 181 16.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 15.1 22.68 1 48 0 0
#> 91.1 5.33 1 61 0 1
#> 5.1 16.43 1 51 0 1
#> 136 21.83 1 43 0 1
#> 93.1 10.33 1 52 0 1
#> 153 21.33 1 55 1 0
#> 63.1 22.77 1 31 1 0
#> 157.1 15.10 1 47 0 0
#> 166 19.98 1 48 0 0
#> 51.2 18.23 1 83 0 1
#> 165 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 176 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 116.1 24.00 0 58 0 1
#> 53 24.00 0 32 0 1
#> 126 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 54 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#> 144 24.00 0 28 0 1
#> 2 24.00 0 9 0 0
#> 9 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 47 24.00 0 38 0 1
#> 47.1 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 144.1 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 163 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 132.1 24.00 0 55 0 0
#> 62 24.00 0 71 0 0
#> 21 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 46.1 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 9.1 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 35.1 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 147.2 24.00 0 76 1 0
#> 120.1 24.00 0 68 0 1
#> 103.1 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 122 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 165.1 24.00 0 47 0 0
#> 9.2 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 165.2 24.00 0 47 0 0
#> 53.2 24.00 0 32 0 1
#> 115 24.00 0 NA 1 0
#> 151 24.00 0 42 0 0
#> 135 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 131 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 94.1 24.00 0 51 0 1
#> 35.2 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 115.2 24.00 0 NA 1 0
#> 112 24.00 0 61 0 0
#> 132.2 24.00 0 55 0 0
#> 135.1 24.00 0 58 1 0
#> 27 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 143.1 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 103.2 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 73 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 162 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 33 24.00 0 53 0 0
#> 74.1 24.00 0 43 0 1
#> 147.3 24.00 0 76 1 0
#> 87 24.00 0 27 0 0
#> 172.1 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.110 NA NA NA
#> 2 age, Cure model -0.00665 NA NA NA
#> 3 grade_ii, Cure model 0.334 NA NA NA
#> 4 grade_iii, Cure model 0.991 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00705 NA NA NA
#> 2 grade_ii, Survival model 0.672 NA NA NA
#> 3 grade_iii, Survival model 0.625 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.110212 -0.006654 0.334314 0.990500
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 248.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.110211978 -0.006653756 0.334313916 0.990500426
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007048959 0.671690411 0.625055912
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.38218016 0.98722301 0.63257144 0.65664710 0.92822371 0.96963937
#> [7] 0.38218016 0.96515150 0.57152581 0.87846072 0.99575787 0.33878817
#> [13] 0.63257144 0.76020704 0.93298201 0.95613064 0.36812370 0.60675606
#> [19] 0.30596593 0.63257144 0.97849982 0.52415302 0.81371138 0.79092756
#> [25] 0.77272442 0.79685835 0.58943033 0.70027910 0.78491083 0.53380182
#> [31] 0.62395755 0.58061291 0.84141653 0.07186453 0.90401754 0.98287581
#> [37] 0.55267918 0.58943033 0.86800134 0.24204764 0.73458030 0.89391475
#> [43] 0.30596593 0.67881027 0.86274567 0.90401754 0.65664710 0.71423871
#> [49] 0.93770041 0.88880852 0.74114903 0.45813723 0.83592634 0.76020704
#> [55] 0.43396944 0.60675606 0.07186453 0.47026074 0.88364517 0.15443871
#> [61] 0.94241240 0.24204764 0.33878817 0.86800134 0.70726948 0.69316614
#> [67] 0.91864015 0.28478360 0.91864015 0.90401754 0.15443871 0.79685835
#> [73] 0.53380182 0.83037911 0.84141653 0.81929971 0.72790623 0.94241240
#> [79] 0.85743600 0.49322044 0.74114903 0.67881027 0.97408440 0.15443871
#> [85] 0.72112434 0.85211971 0.40924783 0.94241240 0.79685835 0.89897362
#> [91] 0.75389221 0.50395554 0.43396944 0.98722301 0.77272442 0.48194967
#> [97] 0.95613064 0.51424108 0.40924783 0.81929971 0.56213429 0.65664710
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 113 91 108 51 107 16 113.1 187 55 140 127 69 108.1
#> 22.86 5.33 18.29 18.23 11.18 8.71 22.86 9.92 19.34 12.68 3.53 23.23 18.29
#> 85 159 93 92 8 129 108.2 77 99 18 167 5 29
#> 16.44 10.55 10.33 22.92 18.43 23.41 18.29 7.27 21.19 15.21 15.55 16.43 15.45
#> 179 134 125 68 88 97 13 24 49 25 150 179.1 14
#> 18.63 17.81 15.65 20.62 18.37 19.14 14.34 23.89 12.19 6.32 20.33 18.63 12.89
#> 86 106 42 129.1 41 123 49.1 51.1 117 10 37 171 169
#> 23.81 16.67 12.43 23.41 18.02 13.00 12.19 18.23 17.46 10.53 12.52 16.57 22.41
#> 57 85.1 15 8.1 24.1 194 177 78 52 86.1 69.1 14.1 184
#> 14.46 16.44 22.68 18.43 23.89 22.40 12.53 23.88 10.42 23.81 23.23 12.89 17.77
#> 40 43 168 43.1 49.2 78.1 29.1 68.1 180 13.1 157 45 52.1
#> 18.00 12.10 23.72 12.10 12.19 23.88 15.45 20.62 14.82 14.34 15.10 17.42 10.42
#> 155 197 171.1 41.1 149 78.2 111 60 63 52.2 29.2 56 181
#> 13.08 21.60 16.57 18.02 8.37 23.88 17.45 13.15 22.77 10.42 15.45 12.21 16.46
#> 139 15.1 91.1 5.1 136 93.1 153 63.1 157.1 166 51.2 165 143
#> 21.49 22.68 5.33 16.43 21.83 10.33 21.33 22.77 15.10 19.98 18.23 24.00 24.00
#> 116 176 109 182 116.1 53 126 67 54 132 144 2 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 47 47.1 104 103 144.1 12 102 163 28 138 119 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 21 46 46.1 160 185 35 118 9.1 141 31 120 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.1 35.1 74 147.2 120.1 103.1 172 75 122 142 165.1 9.2 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.2 53.2 151 135 94 131 141.1 12.1 94.1 35.2 112 132.2 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 80 143.1 71 137 103.2 156 176.1 178 200 162 11 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 147.3 87 172.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[66]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006313494 0.442926970 0.251733880
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.4748443 0.0169093 -0.5922694
#> grade_iii, Cure model
#> 0.2777032
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 61 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 129 23.41 1 53 1 0
#> 5 16.43 1 51 0 1
#> 4 17.64 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 24 23.89 1 38 0 0
#> 77 7.27 1 67 0 1
#> 145 10.07 1 65 1 0
#> 199 19.81 1 NA 0 1
#> 169 22.41 1 46 0 0
#> 128 20.35 1 35 0 1
#> 180 14.82 1 37 0 0
#> 150 20.33 1 48 0 0
#> 153 21.33 1 55 1 0
#> 189 10.51 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 96 14.54 1 33 0 1
#> 10 10.53 1 34 0 0
#> 29 15.45 1 68 1 0
#> 13 14.34 1 54 0 1
#> 91 5.33 1 61 0 1
#> 69 23.23 1 25 0 1
#> 153.1 21.33 1 55 1 0
#> 168 23.72 1 70 0 0
#> 183 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 108 18.29 1 39 0 1
#> 58 19.34 1 39 0 0
#> 111 17.45 1 47 0 1
#> 50 10.02 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 129.1 23.41 1 53 1 0
#> 183.1 9.24 1 67 1 0
#> 5.1 16.43 1 51 0 1
#> 70 7.38 1 30 1 0
#> 107 11.18 1 54 1 0
#> 16 8.71 1 71 0 1
#> 169.1 22.41 1 46 0 0
#> 169.2 22.41 1 46 0 0
#> 167 15.55 1 56 1 0
#> 96.1 14.54 1 33 0 1
#> 106 16.67 1 49 1 0
#> 51.1 18.23 1 83 0 1
#> 42 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 129.2 23.41 1 53 1 0
#> 180.1 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 184 17.77 1 38 0 0
#> 86 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 107.1 11.18 1 54 1 0
#> 70.1 7.38 1 30 1 0
#> 177 12.53 1 75 0 0
#> 180.2 14.82 1 37 0 0
#> 39.1 15.59 1 37 0 1
#> 66 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 55 19.34 1 69 0 1
#> 51.2 18.23 1 83 0 1
#> 153.2 21.33 1 55 1 0
#> 13.1 14.34 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 123 13.00 1 44 1 0
#> 15.1 22.68 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 90 20.94 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 188.2 16.16 1 46 0 1
#> 154 12.63 1 20 1 0
#> 52 10.42 1 52 0 1
#> 106.1 16.67 1 49 1 0
#> 157 15.10 1 47 0 0
#> 140 12.68 1 59 1 0
#> 190 20.81 1 42 1 0
#> 155 13.08 1 26 0 0
#> 8 18.43 1 32 0 0
#> 58.1 19.34 1 39 0 0
#> 190.1 20.81 1 42 1 0
#> 106.2 16.67 1 49 1 0
#> 117 17.46 1 26 0 1
#> 36.1 21.19 1 48 0 1
#> 69.1 23.23 1 25 0 1
#> 123.1 13.00 1 44 1 0
#> 153.3 21.33 1 55 1 0
#> 197 21.60 1 69 1 0
#> 51.3 18.23 1 83 0 1
#> 86.1 23.81 1 58 0 1
#> 10.1 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 42.1 12.43 1 49 0 1
#> 164 23.60 1 76 0 1
#> 8.1 18.43 1 32 0 0
#> 101 9.97 1 10 0 1
#> 113 22.86 1 34 0 0
#> 177.1 12.53 1 75 0 0
#> 25 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 69.2 23.23 1 25 0 1
#> 55.1 19.34 1 69 0 1
#> 136.1 21.83 1 43 0 1
#> 100.1 16.07 1 60 0 0
#> 105 19.75 1 60 0 0
#> 113.1 22.86 1 34 0 0
#> 158 20.14 1 74 1 0
#> 47 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 196 24.00 0 19 0 0
#> 80 24.00 0 41 0 0
#> 172 24.00 0 41 0 0
#> 196.1 24.00 0 19 0 0
#> 47.1 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 174 24.00 0 49 1 0
#> 3 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 122 24.00 0 66 0 0
#> 174.1 24.00 0 49 1 0
#> 118 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 31 24.00 0 36 0 1
#> 148 24.00 0 61 1 0
#> 156.1 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 118.1 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 121 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 47.2 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 172.1 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 27 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 144.1 24.00 0 28 0 1
#> 156.2 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 161.1 24.00 0 45 0 0
#> 103.1 24.00 0 56 1 0
#> 62 24.00 0 71 0 0
#> 73.1 24.00 0 NA 0 1
#> 1.1 24.00 0 23 1 0
#> 48 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 103.2 24.00 0 56 1 0
#> 48.1 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 27.1 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 53.1 24.00 0 32 0 1
#> 75 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 160.1 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 9 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 31.1 24.00 0 36 0 1
#> 176.1 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 176.2 24.00 0 43 0 1
#> 152.1 24.00 0 36 0 1
#> 47.3 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 28 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 191 24.00 0 60 0 1
#> 71.1 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 141.1 24.00 0 44 1 0
#> 165.2 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 94.1 24.00 0 51 0 1
#> 120 24.00 0 68 0 1
#> 47.4 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.475 NA NA NA
#> 2 age, Cure model 0.0169 NA NA NA
#> 3 grade_ii, Cure model -0.592 NA NA NA
#> 4 grade_iii, Cure model 0.278 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00631 NA NA NA
#> 2 grade_ii, Survival model 0.443 NA NA NA
#> 3 grade_iii, Survival model 0.252 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.47484 0.01691 -0.59227 0.27770
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 255.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.4748443 0.0169093 -0.5922694 0.2777032
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006313494 0.442926970 0.251733880
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.849575881 0.889745071 0.542323518 0.052405373 0.522927650 0.232025557
#> [7] 0.003241872 0.969960428 0.899830839 0.133486434 0.277302851 0.649984933
#> [13] 0.286403199 0.197349045 0.397652748 0.679670275 0.859611833 0.620354746
#> [19] 0.709613675 0.989987133 0.076266468 0.197349045 0.025163003 0.919971769
#> [25] 0.503580543 0.378713446 0.314034819 0.455101155 0.169375261 0.052405373
#> [31] 0.919971769 0.522927650 0.950043371 0.829637036 0.939970848 0.133486434
#> [37] 0.133486434 0.610476865 0.679670275 0.474798340 0.397652748 0.799555314
#> [43] 0.590851497 0.503580543 0.052405373 0.649984933 0.699581576 0.025163003
#> [49] 0.435469492 0.011556977 0.571214253 0.829637036 0.950043371 0.779557814
#> [55] 0.649984933 0.590851497 0.159884103 0.819580886 0.314034819 0.397652748
#> [61] 0.197349045 0.709613675 0.116155585 0.739659347 0.116155585 0.542323518
#> [67] 0.250136190 0.378713446 0.542323518 0.769591179 0.879656474 0.474798340
#> [73] 0.630230475 0.759576230 0.259382791 0.729583922 0.350305664 0.314034819
#> [79] 0.259382791 0.474798340 0.445295221 0.232025557 0.076266468 0.739659347
#> [85] 0.197349045 0.187867081 0.397652748 0.011556977 0.859611833 0.464916403
#> [91] 0.799555314 0.042268806 0.350305664 0.909912870 0.099478559 0.779557814
#> [97] 0.979986898 0.369119763 0.630230475 0.076266468 0.314034819 0.169375261
#> [103] 0.571214253 0.304763253 0.099478559 0.295579796 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 159 61 188 129 5 36 24 77 145 169 128 180 150
#> 10.55 10.12 16.16 23.41 16.43 21.19 23.89 7.27 10.07 22.41 20.35 14.82 20.33
#> 153 51 96 10 29 13 91 69 153.1 168 183 192 108
#> 21.33 18.23 14.54 10.53 15.45 14.34 5.33 23.23 21.33 23.72 9.24 16.44 18.29
#> 58 111 136 129.1 183.1 5.1 70 107 16 169.1 169.2 167 96.1
#> 19.34 17.45 21.83 23.41 9.24 16.43 7.38 11.18 8.71 22.41 22.41 15.55 14.54
#> 106 51.1 42 39 85 129.2 180.1 57 168.1 184 86 100 107.1
#> 16.67 18.23 12.43 15.59 16.44 23.41 14.82 14.46 23.72 17.77 23.81 16.07 11.18
#> 70.1 177 180.2 39.1 66 49 55 51.2 153.2 13.1 15 123 15.1
#> 7.38 12.53 14.82 15.59 22.13 12.19 19.34 18.23 21.33 14.34 22.68 13.00 22.68
#> 188.1 90 108.1 188.2 154 52 106.1 157 140 190 155 8 58.1
#> 16.16 20.94 18.29 16.16 12.63 10.42 16.67 15.10 12.68 20.81 13.08 18.43 19.34
#> 190.1 106.2 117 36.1 69.1 123.1 153.3 197 51.3 86.1 10.1 23 42.1
#> 20.81 16.67 17.46 21.19 23.23 13.00 21.33 21.60 18.23 23.81 10.53 16.92 12.43
#> 164 8.1 101 113 177.1 25 88 157.1 69.2 55.1 136.1 100.1 105
#> 23.60 18.43 9.97 22.86 12.53 6.32 18.37 15.10 23.23 19.34 21.83 16.07 19.75
#> 113.1 158 47 65 176 198 196 80 172 196.1 47.1 161 156
#> 22.86 20.14 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 144 174 3 151 122 174.1 118 31 148 156.1 67 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 121 122.1 1 47.2 200 165 54 172.1 165.1 27 182 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 135 161.1 103.1 62 1.1 48 53 103.2 48.1 7 173 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 152 142 53.1 75 138 146 22 193 160.1 138.1 71 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 31.1 176.1 147 176.2 152.1 47.3 141 148.1 28 94 191 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 141.1 165.2 163 46 94.1 120 47.4 143 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[67]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01009733 0.73670111 0.64097061
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86266482 0.01449300 -0.05730324
#> grade_iii, Cure model
#> 0.89225810
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 89 11.44 1 NA 0 0
#> 168 23.72 1 70 0 0
#> 96 14.54 1 33 0 1
#> 77 7.27 1 67 0 1
#> 18 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 127 3.53 1 62 0 1
#> 96.1 14.54 1 33 0 1
#> 159 10.55 1 50 0 1
#> 130 16.47 1 53 0 1
#> 63 22.77 1 31 1 0
#> 130.1 16.47 1 53 0 1
#> 130.2 16.47 1 53 0 1
#> 69 23.23 1 25 0 1
#> 149 8.37 1 33 1 0
#> 50 10.02 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 45 17.42 1 54 0 1
#> 127.1 3.53 1 62 0 1
#> 16 8.71 1 71 0 1
#> 159.1 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 60 13.15 1 38 1 0
#> 127.2 3.53 1 62 0 1
#> 113 22.86 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 130.3 16.47 1 53 0 1
#> 114.1 13.68 1 NA 0 0
#> 171 16.57 1 41 0 1
#> 24 23.89 1 38 0 0
#> 114.2 13.68 1 NA 0 0
#> 171.1 16.57 1 41 0 1
#> 197 21.60 1 69 1 0
#> 68 20.62 1 44 0 0
#> 136 21.83 1 43 0 1
#> 56 12.21 1 60 0 0
#> 45.1 17.42 1 54 0 1
#> 23 16.92 1 61 0 0
#> 68.1 20.62 1 44 0 0
#> 130.4 16.47 1 53 0 1
#> 114.3 13.68 1 NA 0 0
#> 130.5 16.47 1 53 0 1
#> 57 14.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 106 16.67 1 49 1 0
#> 81 14.06 1 34 0 0
#> 30 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 8 18.43 1 32 0 0
#> 97 19.14 1 65 0 1
#> 188 16.16 1 46 0 1
#> 18.1 15.21 1 49 1 0
#> 13 14.34 1 54 0 1
#> 183 9.24 1 67 1 0
#> 58 19.34 1 39 0 0
#> 150 20.33 1 48 0 0
#> 24.1 23.89 1 38 0 0
#> 139 21.49 1 63 1 0
#> 37 12.52 1 57 1 0
#> 42 12.43 1 49 0 1
#> 130.6 16.47 1 53 0 1
#> 180 14.82 1 37 0 0
#> 4 17.64 1 NA 0 1
#> 81.1 14.06 1 34 0 0
#> 45.2 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 145 10.07 1 65 1 0
#> 49 12.19 1 48 1 0
#> 123 13.00 1 44 1 0
#> 14 12.89 1 21 0 0
#> 128 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 37.1 12.52 1 57 1 0
#> 130.7 16.47 1 53 0 1
#> 171.2 16.57 1 41 0 1
#> 150.1 20.33 1 48 0 0
#> 134.1 17.81 1 47 1 0
#> 13.1 14.34 1 54 0 1
#> 88 18.37 1 47 0 0
#> 41 18.02 1 40 1 0
#> 85 16.44 1 36 0 0
#> 68.2 20.62 1 44 0 0
#> 194 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 110 17.56 1 65 0 1
#> 192 16.44 1 31 1 0
#> 60.1 13.15 1 38 1 0
#> 136.1 21.83 1 43 0 1
#> 4.1 17.64 1 NA 0 1
#> 50.1 10.02 1 NA 1 0
#> 56.1 12.21 1 60 0 0
#> 66 22.13 1 53 0 0
#> 181 16.46 1 45 0 1
#> 55.1 19.34 1 69 0 1
#> 41.1 18.02 1 40 1 0
#> 199 19.81 1 NA 0 1
#> 42.1 12.43 1 49 0 1
#> 183.1 9.24 1 67 1 0
#> 91.1 5.33 1 61 0 1
#> 111 17.45 1 47 0 1
#> 51 18.23 1 83 0 1
#> 158 20.14 1 74 1 0
#> 59 10.16 1 NA 1 0
#> 68.3 20.62 1 44 0 0
#> 108 18.29 1 39 0 1
#> 128.1 20.35 1 35 0 1
#> 150.2 20.33 1 48 0 0
#> 18.2 15.21 1 49 1 0
#> 30.1 17.43 1 78 0 0
#> 181.1 16.46 1 45 0 1
#> 60.2 13.15 1 38 1 0
#> 6 15.64 1 39 0 0
#> 82 24.00 0 34 0 0
#> 198 24.00 0 66 0 1
#> 178 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 148 24.00 0 61 1 0
#> 165 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 74 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 143 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 74.1 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 182 24.00 0 35 0 0
#> 193 24.00 0 45 0 1
#> 174 24.00 0 49 1 0
#> 1 24.00 0 23 1 0
#> 20 24.00 0 46 1 0
#> 132 24.00 0 55 0 0
#> 72 24.00 0 40 0 1
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 7 24.00 0 37 1 0
#> 109.1 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 102.1 24.00 0 49 0 0
#> 173 24.00 0 19 0 1
#> 163.1 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 148.1 24.00 0 61 1 0
#> 137 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#> 138 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 121.1 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 196 24.00 0 19 0 0
#> 119 24.00 0 17 0 0
#> 28 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 151.1 24.00 0 42 0 0
#> 112 24.00 0 61 0 0
#> 121.2 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 138.1 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 191.1 24.00 0 60 0 1
#> 62.1 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 2.1 24.00 0 9 0 0
#> 19.1 24.00 0 57 0 1
#> 118 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 34.1 24.00 0 36 0 0
#> 94.1 24.00 0 51 0 1
#> 160.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 11 24.00 0 42 0 1
#> 17.1 24.00 0 38 0 1
#> 22.1 24.00 0 52 1 0
#> 151.2 24.00 0 42 0 0
#> 200.2 24.00 0 64 0 0
#> 82.1 24.00 0 34 0 0
#> 82.2 24.00 0 34 0 0
#> 95.1 24.00 0 68 0 1
#> 119.1 24.00 0 17 0 0
#> 3 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 137.1 24.00 0 45 1 0
#> 22.2 24.00 0 52 1 0
#> 137.2 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.863 NA NA NA
#> 2 age, Cure model 0.0145 NA NA NA
#> 3 grade_ii, Cure model -0.0573 NA NA NA
#> 4 grade_iii, Cure model 0.892 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0101 NA NA NA
#> 2 grade_ii, Survival model 0.737 NA NA NA
#> 3 grade_iii, Survival model 0.641 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86266 0.01449 -0.05730 0.89226
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 250.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86266482 0.01449300 -0.05730324 0.89225810
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01009733 0.73670111 0.64097061
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.19548112 0.86668827 0.97867605 0.84320008 0.95983492 0.98953008
#> [7] 0.86668827 0.94809627 0.76131330 0.30655821 0.76131330 0.76131330
#> [13] 0.23911818 0.97497062 0.44772328 0.71079243 0.98953008 0.97123801
#> [19] 0.94809627 0.98234352 0.89820650 0.98953008 0.27368479 0.76131330
#> [25] 0.74320623 0.09890175 0.74320623 0.41691766 0.46151814 0.38073117
#> [31] 0.93601407 0.71079243 0.73031205 0.46151814 0.76131330 0.76131330
#> [37] 0.87588792 0.66729382 0.73682756 0.88934742 0.69684372 0.57861565
#> [43] 0.61601902 0.60684409 0.82837877 0.84320008 0.88045205 0.96370370
#> [49] 0.57861565 0.53455382 0.09890175 0.43312514 0.91959078 0.92787921
#> [55] 0.76131330 0.86199379 0.88934742 0.71079243 0.82335657 0.95594892
#> [61] 0.94409047 0.91107008 0.91533277 0.51111070 0.83334019 0.91959078
#> [67] 0.76131330 0.74320623 0.53455382 0.66729382 0.88045205 0.62514212
#> [73] 0.65142355 0.81318171 0.46151814 0.33397857 0.85728770 0.68232147
#> [79] 0.81318171 0.89820650 0.38073117 0.93601407 0.35789441 0.80285863
#> [85] 0.57861565 0.65142355 0.92787921 0.96370370 0.98234352 0.68966100
#> [91] 0.64299997 0.56797532 0.46151814 0.63418508 0.51111070 0.53455382
#> [97] 0.84320008 0.69684372 0.80285863 0.89820650 0.83827713 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 168 96 77 18 101 127 96.1 159 130 63 130.1 130.2 69
#> 23.72 14.54 7.27 15.21 9.97 3.53 14.54 10.55 16.47 22.77 16.47 16.47 23.23
#> 149 99 45 127.1 16 159.1 91 60 127.2 113 130.3 171 24
#> 8.37 21.19 17.42 3.53 8.71 10.55 5.33 13.15 3.53 22.86 16.47 16.57 23.89
#> 171.1 197 68 136 56 45.1 23 68.1 130.4 130.5 57 134 106
#> 16.57 21.60 20.62 21.83 12.21 17.42 16.92 20.62 16.47 16.47 14.46 17.81 16.67
#> 81 30 55 8 97 188 18.1 13 183 58 150 24.1 139
#> 14.06 17.43 19.34 18.43 19.14 16.16 15.21 14.34 9.24 19.34 20.33 23.89 21.49
#> 37 42 130.6 180 81.1 45.2 79 145 49 123 14 128 100
#> 12.52 12.43 16.47 14.82 14.06 17.42 16.23 10.07 12.19 13.00 12.89 20.35 16.07
#> 37.1 130.7 171.2 150.1 134.1 13.1 88 41 85 68.2 194 157 110
#> 12.52 16.47 16.57 20.33 17.81 14.34 18.37 18.02 16.44 20.62 22.40 15.10 17.56
#> 192 60.1 136.1 56.1 66 181 55.1 41.1 42.1 183.1 91.1 111 51
#> 16.44 13.15 21.83 12.21 22.13 16.46 19.34 18.02 12.43 9.24 5.33 17.45 18.23
#> 158 68.3 108 128.1 150.2 18.2 30.1 181.1 60.2 6 82 198 178
#> 20.14 20.62 18.29 20.35 20.33 15.21 17.43 16.46 13.15 15.64 24.00 24.00 24.00
#> 33 19 148 165 135 74 62 84 102 143 34 146 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 182 193 174 1 20 132 72 109 141 162 121 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 71 163 191 102.1 173 163.1 151 148.1 137 22 200 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 121.1 47 185 2 196 119 28 94 151.1 112 121.2 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 138.1 95 53 191.1 62.1 160 35 186 31 176 2.1 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 17 34.1 94.1 160.1 21 11 17.1 22.1 151.2 200.2 82.1 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 119.1 3 11.1 137.1 22.2 137.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[68]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005191936 0.560305244 0.290236258
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.1276061 0.0192017 0.3660168
#> grade_iii, Cure model
#> 0.9246577
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 111 17.45 1 47 0 1
#> 195 11.76 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 10 10.53 1 34 0 0
#> 158 20.14 1 74 1 0
#> 42 12.43 1 49 0 1
#> 194 22.40 1 38 0 1
#> 123 13.00 1 44 1 0
#> 39 15.59 1 37 0 1
#> 107 11.18 1 54 1 0
#> 195.1 11.76 1 NA 1 0
#> 158.1 20.14 1 74 1 0
#> 36 21.19 1 48 0 1
#> 76 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 37 12.52 1 57 1 0
#> 5 16.43 1 51 0 1
#> 107.1 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 23 16.92 1 61 0 0
#> 32 20.90 1 37 1 0
#> 171 16.57 1 41 0 1
#> 177 12.53 1 75 0 0
#> 175.1 21.91 1 43 0 0
#> 36.1 21.19 1 48 0 1
#> 15 22.68 1 48 0 0
#> 110 17.56 1 65 0 1
#> 195.2 11.76 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 37.1 12.52 1 57 1 0
#> 133 14.65 1 57 0 0
#> 139 21.49 1 63 1 0
#> 49 12.19 1 48 1 0
#> 23.1 16.92 1 61 0 0
#> 149 8.37 1 33 1 0
#> 108 18.29 1 39 0 1
#> 195.3 11.76 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 169 22.41 1 46 0 0
#> 25 6.32 1 34 1 0
#> 5.1 16.43 1 51 0 1
#> 192 16.44 1 31 1 0
#> 96 14.54 1 33 0 1
#> 177.1 12.53 1 75 0 0
#> 149.1 8.37 1 33 1 0
#> 50 10.02 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 23.2 16.92 1 61 0 0
#> 63 22.77 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 86 23.81 1 58 0 1
#> 155 13.08 1 26 0 0
#> 170 19.54 1 43 0 1
#> 136 21.83 1 43 0 1
#> 134.1 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 181 16.46 1 45 0 1
#> 157 15.10 1 47 0 0
#> 29 15.45 1 68 1 0
#> 175.2 21.91 1 43 0 0
#> 183 9.24 1 67 1 0
#> 106 16.67 1 49 1 0
#> 129 23.41 1 53 1 0
#> 96.1 14.54 1 33 0 1
#> 181.1 16.46 1 45 0 1
#> 42.1 12.43 1 49 0 1
#> 56 12.21 1 60 0 0
#> 58 19.34 1 39 0 0
#> 43 12.10 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 36.2 21.19 1 48 0 1
#> 194.1 22.40 1 38 0 1
#> 66 22.13 1 53 0 0
#> 114 13.68 1 NA 0 0
#> 108.1 18.29 1 39 0 1
#> 183.1 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 179 18.63 1 42 0 0
#> 192.1 16.44 1 31 1 0
#> 36.3 21.19 1 48 0 1
#> 15.1 22.68 1 48 0 0
#> 175.3 21.91 1 43 0 0
#> 130 16.47 1 53 0 1
#> 92 22.92 1 47 0 1
#> 37.2 12.52 1 57 1 0
#> 91 5.33 1 61 0 1
#> 101 9.97 1 10 0 1
#> 155.1 13.08 1 26 0 0
#> 140 12.68 1 59 1 0
#> 166 19.98 1 48 0 0
#> 6 15.64 1 39 0 0
#> 111.1 17.45 1 47 0 1
#> 91.1 5.33 1 61 0 1
#> 114.1 13.68 1 NA 0 0
#> 157.1 15.10 1 47 0 0
#> 183.2 9.24 1 67 1 0
#> 111.2 17.45 1 47 0 1
#> 111.3 17.45 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 43.1 12.10 1 61 0 1
#> 96.2 14.54 1 33 0 1
#> 99 21.19 1 38 0 1
#> 39.2 15.59 1 37 0 1
#> 105 19.75 1 60 0 0
#> 90 20.94 1 50 0 1
#> 78 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 107.2 11.18 1 54 1 0
#> 170.1 19.54 1 43 0 1
#> 83 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 173 24.00 0 19 0 1
#> 193 24.00 0 45 0 1
#> 84 24.00 0 39 0 1
#> 135 24.00 0 58 1 0
#> 173.1 24.00 0 19 0 1
#> 121 24.00 0 57 1 0
#> 80.1 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#> 67 24.00 0 25 0 0
#> 131.1 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 3 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 147 24.00 0 76 1 0
#> 74 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 62.1 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 121.1 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 67.1 24.00 0 25 0 0
#> 62.2 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 73 24.00 0 NA 0 1
#> 21 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 143 24.00 0 51 0 0
#> 173.2 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 84.1 24.00 0 39 0 1
#> 34 24.00 0 36 0 0
#> 132 24.00 0 55 0 0
#> 98 24.00 0 34 1 0
#> 20 24.00 0 46 1 0
#> 144.1 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 11.1 24.00 0 42 0 1
#> 62.3 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 62.4 24.00 0 71 0 0
#> 87.1 24.00 0 27 0 0
#> 185 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 103 24.00 0 56 1 0
#> 46.1 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 122 24.00 0 66 0 0
#> 11.2 24.00 0 42 0 1
#> 20.1 24.00 0 46 1 0
#> 74.1 24.00 0 43 0 1
#> 83.1 24.00 0 6 0 0
#> 176 24.00 0 43 0 1
#> 137.1 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 147.1 24.00 0 76 1 0
#> 148.1 24.00 0 61 1 0
#> 160.1 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 44 24.00 0 56 0 0
#> 143.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 2 24.00 0 9 0 0
#> 71 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 11.3 24.00 0 42 0 1
#> 82 24.00 0 34 0 0
#> 17 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 144.2 24.00 0 28 0 1
#> 147.2 24.00 0 76 1 0
#> 75.1 24.00 0 21 1 0
#> 2.1 24.00 0 9 0 0
#> 82.1 24.00 0 34 0 0
#> 11.4 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.13 NA NA NA
#> 2 age, Cure model 0.0192 NA NA NA
#> 3 grade_ii, Cure model 0.366 NA NA NA
#> 4 grade_iii, Cure model 0.925 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00519 NA NA NA
#> 2 grade_ii, Survival model 0.560 NA NA NA
#> 3 grade_iii, Survival model 0.290 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1276 0.0192 0.3660 0.9247
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 250.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1276061 0.0192017 0.3660168 0.9246577
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005191936 0.560305244 0.290236258
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.59616500 0.73166860 0.93763170 0.46212212 0.88353761 0.24252700
#> [7] 0.83264483 0.74567505 0.92010551 0.46212212 0.37838172 0.52736850
#> [13] 0.62741691 0.86497766 0.71037658 0.92010551 0.28690240 0.63530321
#> [19] 0.44139748 0.66601503 0.85218666 0.28690240 0.37838172 0.19357569
#> [25] 0.58788078 0.45189971 0.86497766 0.79307604 0.35314207 0.90198130
#> [31] 0.63530321 0.97215689 0.55394819 0.52736850 0.22601225 0.98337079
#> [37] 0.71037658 0.69592947 0.79979415 0.85218666 0.97215689 0.74567505
#> [43] 0.63530321 0.17573767 0.57122556 0.10589227 0.81949101 0.49997478
#> [49] 0.33952190 0.57122556 0.72460895 0.68115826 0.77289618 0.76611292
#> [55] 0.28690240 0.95517399 0.65835388 0.13380144 0.79979415 0.68115826
#> [61] 0.88353761 0.89582957 0.51820717 0.90808116 0.78633827 0.37838172
#> [67] 0.24252700 0.27200409 0.55394819 0.95517399 0.36605101 0.54506325
#> [73] 0.69592947 0.37838172 0.19357569 0.28690240 0.67361899 0.15576033
#> [79] 0.86497766 0.98895901 0.94932431 0.81949101 0.84572060 0.48104036
#> [85] 0.73867927 0.59616500 0.98895901 0.77289618 0.95517399 0.59616500
#> [91] 0.59616500 0.93763170 0.90808116 0.79979415 0.37838172 0.74567505
#> [97] 0.49054096 0.43060720 0.07061729 0.83918565 0.03107257 0.92010551
#> [103] 0.49997478 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 111 26 10 158 42 194 123 39 107 158.1 36 76 45
#> 17.45 15.77 10.53 20.14 12.43 22.40 13.00 15.59 11.18 20.14 21.19 19.22 17.42
#> 37 5 107.1 175 23 32 171 177 175.1 36.1 15 110 190
#> 12.52 16.43 11.18 21.91 16.92 20.90 16.57 12.53 21.91 21.19 22.68 17.56 20.81
#> 37.1 133 139 49 23.1 149 108 76.1 169 25 5.1 192 96
#> 12.52 14.65 21.49 12.19 16.92 8.37 18.29 19.22 22.41 6.32 16.43 16.44 14.54
#> 177.1 149.1 39.1 23.2 63 134 86 155 170 136 134.1 79 181
#> 12.53 8.37 15.59 16.92 22.77 17.81 23.81 13.08 19.54 21.83 17.81 16.23 16.46
#> 157 29 175.2 183 106 129 96.1 181.1 42.1 56 58 43 180
#> 15.10 15.45 21.91 9.24 16.67 23.41 14.54 16.46 12.43 12.21 19.34 12.10 14.82
#> 36.2 194.1 66 108.1 183.1 153 179 192.1 36.3 15.1 175.3 130 92
#> 21.19 22.40 22.13 18.29 9.24 21.33 18.63 16.44 21.19 22.68 21.91 16.47 22.92
#> 37.2 91 101 155.1 140 166 6 111.1 91.1 157.1 183.2 111.2 111.3
#> 12.52 5.33 9.97 13.08 12.68 19.98 15.64 17.45 5.33 15.10 9.24 17.45 17.45
#> 10.1 43.1 96.2 99 39.2 105 90 78 14 24 107.2 170.1 83
#> 10.53 12.10 14.54 21.19 15.59 19.75 20.94 23.88 12.89 23.89 11.18 19.54 24.00
#> 47 46 80 131 87 173 193 84 135 173.1 121 80.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 67 131.1 144 3 11 147 74 148 62.1 102 121.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 62.2 21 116 143 173.2 137 84.1 34 132 98 20 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 11.1 62.3 75 62.4 87.1 185 72 103 46.1 178 38 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 1 122 11.2 20.1 74.1 83.1 176 137.1 151 35 109 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 160.1 193.1 146 44 143.1 119 2 71 132.1 11.3 82 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 144.2 147.2 75.1 2.1 82.1 11.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[69]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01626354 0.81763077 0.61595191
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.66982039 0.01372424 -0.01248633
#> grade_iii, Cure model
#> 0.82411843
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 89 11.44 1 NA 0 0
#> 10 10.53 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 167 15.55 1 56 1 0
#> 188 16.16 1 46 0 1
#> 42 12.43 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 175 21.91 1 43 0 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 36 21.19 1 48 0 1
#> 171 16.57 1 41 0 1
#> 150 20.33 1 48 0 0
#> 77 7.27 1 67 0 1
#> 179 18.63 1 42 0 0
#> 110 17.56 1 65 0 1
#> 101 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 183 9.24 1 67 1 0
#> 105 19.75 1 60 0 0
#> 164 23.60 1 76 0 1
#> 150.1 20.33 1 48 0 0
#> 110.1 17.56 1 65 0 1
#> 128 20.35 1 35 0 1
#> 52 10.42 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 190 20.81 1 42 1 0
#> 91 5.33 1 61 0 1
#> 41.1 18.02 1 40 1 0
#> 168 23.72 1 70 0 0
#> 170 19.54 1 43 0 1
#> 57 14.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 125 15.65 1 67 1 0
#> 96 14.54 1 33 0 1
#> 164.1 23.60 1 76 0 1
#> 158 20.14 1 74 1 0
#> 184 17.77 1 38 0 0
#> 114.1 13.68 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 39 15.59 1 37 0 1
#> 169 22.41 1 46 0 0
#> 66 22.13 1 53 0 0
#> 177 12.53 1 75 0 0
#> 127 3.53 1 62 0 1
#> 167.1 15.55 1 56 1 0
#> 4 17.64 1 NA 0 1
#> 166.1 19.98 1 48 0 0
#> 30 17.43 1 78 0 0
#> 41.2 18.02 1 40 1 0
#> 175.1 21.91 1 43 0 0
#> 61 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 190.1 20.81 1 42 1 0
#> 158.1 20.14 1 74 1 0
#> 107 11.18 1 54 1 0
#> 41.3 18.02 1 40 1 0
#> 166.2 19.98 1 48 0 0
#> 192 16.44 1 31 1 0
#> 192.1 16.44 1 31 1 0
#> 175.2 21.91 1 43 0 0
#> 4.1 17.64 1 NA 0 1
#> 154.1 12.63 1 20 1 0
#> 190.2 20.81 1 42 1 0
#> 86 23.81 1 58 0 1
#> 4.2 17.64 1 NA 0 1
#> 197 21.60 1 69 1 0
#> 23 16.92 1 61 0 0
#> 139 21.49 1 63 1 0
#> 168.1 23.72 1 70 0 0
#> 14 12.89 1 21 0 0
#> 150.2 20.33 1 48 0 0
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 14.1 12.89 1 21 0 0
#> 136 21.83 1 43 0 1
#> 49 12.19 1 48 1 0
#> 107.1 11.18 1 54 1 0
#> 58 19.34 1 39 0 0
#> 43 12.10 1 61 0 1
#> 49.1 12.19 1 48 1 0
#> 167.2 15.55 1 56 1 0
#> 105.1 19.75 1 60 0 0
#> 66.1 22.13 1 53 0 0
#> 180 14.82 1 37 0 0
#> 26 15.77 1 49 0 1
#> 90 20.94 1 50 0 1
#> 157 15.10 1 47 0 0
#> 36.1 21.19 1 48 0 1
#> 192.2 16.44 1 31 1 0
#> 108 18.29 1 39 0 1
#> 140 12.68 1 59 1 0
#> 180.1 14.82 1 37 0 0
#> 50 10.02 1 NA 1 0
#> 171.1 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 117 17.46 1 26 0 1
#> 78 23.88 1 43 0 0
#> 55 19.34 1 69 0 1
#> 49.2 12.19 1 48 1 0
#> 8 18.43 1 32 0 0
#> 42.1 12.43 1 49 0 1
#> 56 12.21 1 60 0 0
#> 86.1 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 127.1 3.53 1 62 0 1
#> 190.3 20.81 1 42 1 0
#> 187 9.92 1 39 1 0
#> 73 24.00 0 NA 0 1
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 34 24.00 0 36 0 0
#> 64 24.00 0 43 0 0
#> 84 24.00 0 39 0 1
#> 82 24.00 0 34 0 0
#> 38 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 146 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 160 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 196 24.00 0 19 0 0
#> 137 24.00 0 45 1 0
#> 19 24.00 0 57 0 1
#> 122 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 191 24.00 0 60 0 1
#> 82.1 24.00 0 34 0 0
#> 143.1 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 152 24.00 0 36 0 1
#> 122.1 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 143.2 24.00 0 51 0 0
#> 143.3 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 94.1 24.00 0 51 0 1
#> 137.1 24.00 0 45 1 0
#> 12 24.00 0 63 0 0
#> 118 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 82.2 24.00 0 34 0 0
#> 137.2 24.00 0 45 1 0
#> 182 24.00 0 35 0 0
#> 7.1 24.00 0 37 1 0
#> 118.1 24.00 0 44 1 0
#> 38.2 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 156 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 64.1 24.00 0 43 0 0
#> 112 24.00 0 61 0 0
#> 174.1 24.00 0 49 1 0
#> 3 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 83 24.00 0 6 0 0
#> 185 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 173 24.00 0 19 0 1
#> 9 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 62.1 24.00 0 71 0 0
#> 31.1 24.00 0 36 0 1
#> 62.2 24.00 0 71 0 0
#> 115.1 24.00 0 NA 1 0
#> 71 24.00 0 51 0 0
#> 31.2 24.00 0 36 0 1
#> 122.2 24.00 0 66 0 0
#> 132.1 24.00 0 55 0 0
#> 53.1 24.00 0 32 0 1
#> 112.1 24.00 0 61 0 0
#> 80.1 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 160.1 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 38.3 24.00 0 31 1 0
#> 38.4 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 186.1 24.00 0 45 1 0
#> 54.1 24.00 0 53 1 0
#> 138.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.670 NA NA NA
#> 2 age, Cure model 0.0137 NA NA NA
#> 3 grade_ii, Cure model -0.0125 NA NA NA
#> 4 grade_iii, Cure model 0.824 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0163 NA NA NA
#> 2 grade_ii, Survival model 0.818 NA NA NA
#> 3 grade_iii, Survival model 0.616 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66982 0.01372 -0.01249 0.82412
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 252.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.66982039 0.01372424 -0.01248633 0.82411843
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01626354 0.81763077 0.61595191
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8567244807 0.3293674250 0.5461039496 0.5015765161 0.7402156121
#> [6] 0.6363216279 0.0488659653 0.0941290674 0.2862754126 0.1024536507
#> [11] 0.4354967634 0.1655538969 0.9519939155 0.2968277448 0.3806684200
#> [16] 0.9163368581 0.4578102019 0.9400945824 0.2357984941 0.0170082416
#> [21] 0.1655538969 0.3806684200 0.1574566738 0.8686147858 0.8686147858
#> [26] 0.1274138020 0.9639496346 0.3293674250 0.0098437901 0.2555992197
#> [31] 0.6247874658 0.7059156122 0.5237655565 0.6132765657 0.0170082416
#> [36] 0.1905732745 0.3699381415 0.2081454690 0.5349364164 0.0310309176
#> [41] 0.0365899181 0.7286368103 0.9759520212 0.5461039496 0.2081454690
#> [46] 0.4131336614 0.3293674250 0.0488659653 0.9043534961 0.8449038608
#> [51] 0.1274138020 0.1905732745 0.8214862315 0.3293674250 0.2081454690
#> [56] 0.4691674083 0.4691674083 0.0488659653 0.7059156122 0.1274138020
#> [61] 0.0050725791 0.0777357703 0.4242224974 0.0858590348 0.0098437901
#> [66] 0.6710790578 0.1655538969 0.0004204898 0.0004204898 0.0259522157
#> [71] 0.6710790578 0.0698299492 0.7750586992 0.8214862315 0.2657312063
#> [76] 0.8097126619 0.7750586992 0.5461039496 0.2357984941 0.0365899181
#> [81] 0.5904358080 0.5126511601 0.1188183656 0.5791030192 0.1024536507
#> [86] 0.4691674083 0.3184648542 0.6942207064 0.5904358080 0.4354967634
#> [91] 0.6595230655 0.4022547088 0.0026882922 0.2657312063 0.7750586992
#> [96] 0.3075690930 0.7402156121 0.7633108101 0.0050725791 0.8923652227
#> [101] 0.6479452869 0.9759520212 0.1274138020 0.9282310148 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 10 41 167 188 42 81 175 153 76 36 171 150 77
#> 10.53 18.02 15.55 16.16 12.43 14.06 21.91 21.33 19.22 21.19 16.57 20.33 7.27
#> 179 110 101 130 183 105 164 150.1 110.1 128 52 52.1 190
#> 18.63 17.56 9.97 16.47 9.24 19.75 23.60 20.33 17.56 20.35 10.42 10.42 20.81
#> 91 41.1 168 170 57 154 125 96 164.1 158 184 166 39
#> 5.33 18.02 23.72 19.54 14.46 12.63 15.65 14.54 23.60 20.14 17.77 19.98 15.59
#> 169 66 177 127 167.1 166.1 30 41.2 175.1 61 159 190.1 158.1
#> 22.41 22.13 12.53 3.53 15.55 19.98 17.43 18.02 21.91 10.12 10.55 20.81 20.14
#> 107 41.3 166.2 192 192.1 175.2 154.1 190.2 86 197 23 139 168.1
#> 11.18 18.02 19.98 16.44 16.44 21.91 12.63 20.81 23.81 21.60 16.92 21.49 23.72
#> 14 150.2 24 24.1 92 14.1 136 49 107.1 58 43 49.1 167.2
#> 12.89 20.33 23.89 23.89 22.92 12.89 21.83 12.19 11.18 19.34 12.10 12.19 15.55
#> 105.1 66.1 180 26 90 157 36.1 192.2 108 140 180.1 171.1 123
#> 19.75 22.13 14.82 15.77 20.94 15.10 21.19 16.44 18.29 12.68 14.82 16.57 13.00
#> 117 78 55 49.2 8 42.1 56 86.1 93 60 127.1 190.3 187
#> 17.46 23.88 19.34 12.19 18.43 12.43 12.21 23.81 10.33 13.15 3.53 20.81 9.92
#> 186 1 34 64 84 82 38 143 103 146 144 17 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 53 196 137 19 122 121 200 191 82.1 143.1 38.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 152 122.1 87 143.2 143.3 94 94.1 137.1 12 118 131 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.2 182 7.1 118.1 38.2 80 138 132 156 95 178 64.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 3 27 48 62 83 185 148 173 9 31 165 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 31.1 62.2 71 31.2 122.2 132.1 53.1 112.1 80.1 198 160.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 38.3 38.4 131.1 186.1 54.1 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[70]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01605113 0.43254089 0.59768529
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.63119995 0.01087944 0.34555008
#> grade_iii, Cure model
#> 0.58286571
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 199 19.81 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 181 16.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 189 10.51 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 187 9.92 1 39 1 0
#> 150.1 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 149 8.37 1 33 1 0
#> 68 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 127 3.53 1 62 0 1
#> 124 9.73 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 45 17.42 1 54 0 1
#> 63 22.77 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 192 16.44 1 31 1 0
#> 68.1 20.62 1 44 0 0
#> 30 17.43 1 78 0 0
#> 140 12.68 1 59 1 0
#> 42 12.43 1 49 0 1
#> 159.1 10.55 1 50 0 1
#> 164 23.60 1 76 0 1
#> 179 18.63 1 42 0 0
#> 140.1 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 154 12.63 1 20 1 0
#> 134 17.81 1 47 1 0
#> 97 19.14 1 65 0 1
#> 30.1 17.43 1 78 0 0
#> 92 22.92 1 47 0 1
#> 179.1 18.63 1 42 0 0
#> 129 23.41 1 53 1 0
#> 127.1 3.53 1 62 0 1
#> 127.2 3.53 1 62 0 1
#> 5 16.43 1 51 0 1
#> 168.1 23.72 1 70 0 0
#> 66 22.13 1 53 0 0
#> 100 16.07 1 60 0 0
#> 51 18.23 1 83 0 1
#> 107.1 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 63.1 22.77 1 31 1 0
#> 127.3 3.53 1 62 0 1
#> 149.1 8.37 1 33 1 0
#> 123 13.00 1 44 1 0
#> 70 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 140.2 12.68 1 59 1 0
#> 129.1 23.41 1 53 1 0
#> 180.1 14.82 1 37 0 0
#> 189.1 10.51 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 183 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 140.3 12.68 1 59 1 0
#> 32 20.90 1 37 1 0
#> 56 12.21 1 60 0 0
#> 134.1 17.81 1 47 1 0
#> 41 18.02 1 40 1 0
#> 51.1 18.23 1 83 0 1
#> 14 12.89 1 21 0 0
#> 153.1 21.33 1 55 1 0
#> 159.2 10.55 1 50 0 1
#> 13 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 91 5.33 1 61 0 1
#> 37 12.52 1 57 1 0
#> 61 10.12 1 36 0 1
#> 123.1 13.00 1 44 1 0
#> 111 17.45 1 47 0 1
#> 164.1 23.60 1 76 0 1
#> 13.1 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 190 20.81 1 42 1 0
#> 170 19.54 1 43 0 1
#> 13.2 14.34 1 54 0 1
#> 128 20.35 1 35 0 1
#> 8 18.43 1 32 0 0
#> 39 15.59 1 37 0 1
#> 45.1 17.42 1 54 0 1
#> 10 10.53 1 34 0 0
#> 149.2 8.37 1 33 1 0
#> 181.1 16.46 1 45 0 1
#> 63.2 22.77 1 31 1 0
#> 97.1 19.14 1 65 0 1
#> 168.2 23.72 1 70 0 0
#> 23 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 10.1 10.53 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 4.1 17.64 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 145 10.07 1 65 1 0
#> 42.1 12.43 1 49 0 1
#> 149.3 8.37 1 33 1 0
#> 51.2 18.23 1 83 0 1
#> 183.1 9.24 1 67 1 0
#> 90 20.94 1 50 0 1
#> 26 15.77 1 49 0 1
#> 76 19.22 1 54 0 1
#> 70.1 7.38 1 30 1 0
#> 105 19.75 1 60 0 0
#> 184.1 17.77 1 38 0 0
#> 145.1 10.07 1 65 1 0
#> 29 15.45 1 68 1 0
#> 44 24.00 0 56 0 0
#> 17 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 131 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 48 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 53 24.00 0 32 0 1
#> 95.1 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 74.1 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 118 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 35 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 137 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 116.1 24.00 0 58 0 1
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 147 24.00 0 76 1 0
#> 131.1 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 116.2 24.00 0 58 0 1
#> 147.1 24.00 0 76 1 0
#> 137.1 24.00 0 45 1 0
#> 137.2 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 185.1 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 73.1 24.00 0 NA 0 1
#> 191 24.00 0 60 0 1
#> 193 24.00 0 45 0 1
#> 48.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 67.1 24.00 0 25 0 0
#> 191.1 24.00 0 60 0 1
#> 122 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 87.1 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 165.1 24.00 0 47 0 0
#> 27.1 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 74.2 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 71 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 176 24.00 0 43 0 1
#> 138.1 24.00 0 44 1 0
#> 48.2 24.00 0 31 1 0
#> 95.2 24.00 0 68 0 1
#> 103.1 24.00 0 56 1 0
#> 35.1 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 83.1 24.00 0 6 0 0
#> 191.2 24.00 0 60 0 1
#> 33 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 161 24.00 0 45 0 0
#> 178 24.00 0 52 1 0
#> 62.1 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 119 24.00 0 17 0 0
#> 162 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 84.1 24.00 0 39 0 1
#> 161.1 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 21 24.00 0 47 0 0
#> 186.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.631 NA NA NA
#> 2 age, Cure model 0.0109 NA NA NA
#> 3 grade_ii, Cure model 0.346 NA NA NA
#> 4 grade_iii, Cure model 0.583 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0161 NA NA NA
#> 2 grade_ii, Survival model 0.433 NA NA NA
#> 3 grade_iii, Survival model 0.598 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.63120 0.01088 0.34555 0.58287
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 251.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.63119995 0.01087944 0.34555008 0.58286571
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01605113 0.43254089 0.59768529
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6591587397 0.3391187602 0.0948559974 0.4387898391 0.0205101428
#> [6] 0.8061814558 0.0948559974 0.0001553131 0.8474732285 0.0760552183
#> [11] 0.1769540052 0.9439292342 0.6853742195 0.3075022284 0.0252610769
#> [16] 0.3605272034 0.0760552183 0.2870107197 0.5457164486 0.6205705713
#> [21] 0.6853742195 0.0033653488 0.1526462678 0.5457164486 0.4971233087
#> [26] 0.5950560283 0.2296244693 0.1374613703 0.2870107197 0.0161831448
#> [31] 0.1526462678 0.0089323677 0.9439292342 0.9439292342 0.3714159262
#> [36] 0.0001553131 0.0374662761 0.3823683142 0.1940792454 0.6591587397
#> [41] 0.0424298272 0.0252610769 0.9439292342 0.8474732285 0.5092221177
#> [46] 0.9020919077 0.2480978366 0.5457164486 0.0089323677 0.4387898391
#> [51] 0.2672217846 0.8198771028 0.0477011706 0.5457164486 0.0642525819
#> [56] 0.6461028282 0.2296244693 0.2204029661 0.1940792454 0.5334043175
#> [61] 0.0477011706 0.6853742195 0.4620532818 0.9298685254 0.6077620596
#> [66] 0.7516303640 0.5092221177 0.2770906112 0.0033653488 0.4620532818
#> [71] 0.1225486372 0.0701004743 0.1153453824 0.4620532818 0.0884445448
#> [76] 0.1686106888 0.4047226716 0.3075022284 0.7247337852 0.8474732285
#> [81] 0.3391187602 0.0252610769 0.1374613703 0.0001553131 0.3283214354
#> [86] 0.4272769162 0.7247337852 0.1855110755 0.7925266154 0.7651962625
#> [91] 0.6205705713 0.8474732285 0.1940792454 0.8198771028 0.0584832368
#> [96] 0.3935181717 0.1299544964 0.9020919077 0.1081817900 0.2480978366
#> [101] 0.7651962625 0.4159260126 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000
#>
#> $Time
#> 107 181 150 180 113 187 150.1 168 149 68 88 127 159
#> 11.18 16.46 20.33 14.82 22.86 9.92 20.33 23.72 8.37 20.62 18.37 3.53 10.55
#> 45 63 192 68.1 30 140 42 159.1 164 179 140.1 81 154
#> 17.42 22.77 16.44 20.62 17.43 12.68 12.43 10.55 23.60 18.63 12.68 14.06 12.63
#> 134 97 30.1 92 179.1 129 127.1 127.2 5 168.1 66 100 51
#> 17.81 19.14 17.43 22.92 18.63 23.41 3.53 3.53 16.43 23.72 22.13 16.07 18.23
#> 107.1 175 63.1 127.3 149.1 123 70 184 140.2 129.1 180.1 110 183
#> 11.18 21.91 22.77 3.53 8.37 13.00 7.38 17.77 12.68 23.41 14.82 17.56 9.24
#> 153 140.3 32 56 134.1 41 51.1 14 153.1 159.2 13 91 37
#> 21.33 12.68 20.90 12.21 17.81 18.02 18.23 12.89 21.33 10.55 14.34 5.33 12.52
#> 61 123.1 111 164.1 13.1 58 190 170 13.2 128 8 39 45.1
#> 10.12 13.00 17.45 23.60 14.34 19.34 20.81 19.54 14.34 20.35 18.43 15.59 17.42
#> 10 149.2 181.1 63.2 97.1 168.2 23 157 10.1 108 101 145 42.1
#> 10.53 8.37 16.46 22.77 19.14 23.72 16.92 15.10 10.53 18.29 9.97 10.07 12.43
#> 149.3 51.2 183.1 90 26 76 70.1 105 184.1 145.1 29 44 17
#> 8.37 18.23 9.24 20.94 15.77 19.22 7.38 19.75 17.77 10.07 15.45 24.00 24.00
#> 138 95 200 131 185 151 74 48 7 27 116 53 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 74.1 103 118 35 87 137 172 116.1 186 82 147 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 132 67 116.2 147.1 137.1 137.2 121 185.1 141 62 191 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 80 83 67.1 191.1 122 126 87.1 54 34 165.1 27.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.2 9 173 71 126.1 94 176 138.1 48.2 95.2 103.1 35.1 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 191.2 33 34.1 161 178 62.1 163 148 119 162 198 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 75 21 186.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[71]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00584286 0.19985152 0.27982460
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.127773711 -0.001875895 0.404985021
#> grade_iii, Cure model
#> 0.963420790
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 110 17.56 1 65 0 1
#> 150 20.33 1 48 0 0
#> 40 18.00 1 28 1 0
#> 99 21.19 1 38 0 1
#> 108 18.29 1 39 0 1
#> 167 15.55 1 56 1 0
#> 123 13.00 1 44 1 0
#> 128 20.35 1 35 0 1
#> 158 20.14 1 74 1 0
#> 177 12.53 1 75 0 0
#> 181 16.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 92 22.92 1 47 0 1
#> 166 19.98 1 48 0 0
#> 187 9.92 1 39 1 0
#> 140 12.68 1 59 1 0
#> 101 9.97 1 10 0 1
#> 81 14.06 1 34 0 0
#> 179 18.63 1 42 0 0
#> 6 15.64 1 39 0 0
#> 150.1 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 63 22.77 1 31 1 0
#> 13 14.34 1 54 0 1
#> 39 15.59 1 37 0 1
#> 100 16.07 1 60 0 0
#> 171 16.57 1 41 0 1
#> 79 16.23 1 54 1 0
#> 181.1 16.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 99.1 21.19 1 38 0 1
#> 81.1 14.06 1 34 0 0
#> 10 10.53 1 34 0 0
#> 63.1 22.77 1 31 1 0
#> 123.1 13.00 1 44 1 0
#> 41 18.02 1 40 1 0
#> 169 22.41 1 46 0 0
#> 4 17.64 1 NA 0 1
#> 49 12.19 1 48 1 0
#> 10.1 10.53 1 34 0 0
#> 6.1 15.64 1 39 0 0
#> 169.1 22.41 1 46 0 0
#> 91 5.33 1 61 0 1
#> 199 19.81 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 167.1 15.55 1 56 1 0
#> 24 23.89 1 38 0 0
#> 183 9.24 1 67 1 0
#> 49.1 12.19 1 48 1 0
#> 13.1 14.34 1 54 0 1
#> 110.1 17.56 1 65 0 1
#> 16 8.71 1 71 0 1
#> 40.1 18.00 1 28 1 0
#> 192 16.44 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 127 3.53 1 62 0 1
#> 101.1 9.97 1 10 0 1
#> 41.1 18.02 1 40 1 0
#> 97 19.14 1 65 0 1
#> 184 17.77 1 38 0 0
#> 52 10.42 1 52 0 1
#> 100.1 16.07 1 60 0 0
#> 55 19.34 1 69 0 1
#> 153 21.33 1 55 1 0
#> 16.1 8.71 1 71 0 1
#> 127.1 3.53 1 62 0 1
#> 123.2 13.00 1 44 1 0
#> 43 12.10 1 61 0 1
#> 18 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 55.1 19.34 1 69 0 1
#> 181.2 16.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 183.1 9.24 1 67 1 0
#> 155 13.08 1 26 0 0
#> 96 14.54 1 33 0 1
#> 124 9.73 1 NA 1 0
#> 108.1 18.29 1 39 0 1
#> 81.2 14.06 1 34 0 0
#> 113 22.86 1 34 0 0
#> 4.1 17.64 1 NA 0 1
#> 127.2 3.53 1 62 0 1
#> 57 14.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 127.3 3.53 1 62 0 1
#> 18.1 15.21 1 49 1 0
#> 190.1 20.81 1 42 1 0
#> 155.1 13.08 1 26 0 0
#> 76 19.22 1 54 0 1
#> 140.1 12.68 1 59 1 0
#> 177.1 12.53 1 75 0 0
#> 76.1 19.22 1 54 0 1
#> 145 10.07 1 65 1 0
#> 10.2 10.53 1 34 0 0
#> 25 6.32 1 34 1 0
#> 23 16.92 1 61 0 0
#> 58 19.34 1 39 0 0
#> 140.2 12.68 1 59 1 0
#> 179.1 18.63 1 42 0 0
#> 59 10.16 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 36 21.19 1 48 0 1
#> 15 22.68 1 48 0 0
#> 93 10.33 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 128.1 20.35 1 35 0 1
#> 32 20.90 1 37 1 0
#> 187.1 9.92 1 39 1 0
#> 197 21.60 1 69 1 0
#> 63.2 22.77 1 31 1 0
#> 190.2 20.81 1 42 1 0
#> 54 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 185 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 109 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 193 24.00 0 45 0 1
#> 82 24.00 0 34 0 0
#> 21 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 116 24.00 0 58 0 1
#> 35 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 19 24.00 0 57 0 1
#> 34.1 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 182 24.00 0 35 0 0
#> 31.1 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 112 24.00 0 61 0 0
#> 47 24.00 0 38 0 1
#> 185.1 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 21.2 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 131 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 67 24.00 0 25 0 0
#> 174 24.00 0 49 1 0
#> 73 24.00 0 NA 0 1
#> 46.1 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 22 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 44.1 24.00 0 56 0 0
#> 198 24.00 0 66 0 1
#> 31.2 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 27.1 24.00 0 63 1 0
#> 161.1 24.00 0 45 0 0
#> 34.2 24.00 0 36 0 0
#> 21.3 24.00 0 47 0 0
#> 156 24.00 0 50 1 0
#> 35.1 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 71.1 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 147 24.00 0 76 1 0
#> 174.1 24.00 0 49 1 0
#> 82.1 24.00 0 34 0 0
#> 148.1 24.00 0 61 1 0
#> 178.1 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 98.1 24.00 0 34 1 0
#> 11.1 24.00 0 42 0 1
#> 176 24.00 0 43 0 1
#> 74 24.00 0 43 0 1
#> 191 24.00 0 60 0 1
#> 191.1 24.00 0 60 0 1
#> 122 24.00 0 66 0 0
#> 54.1 24.00 0 53 1 0
#> 7 24.00 0 37 1 0
#> 115.1 24.00 0 NA 1 0
#> 62.1 24.00 0 71 0 0
#> 7.1 24.00 0 37 1 0
#> 118 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 46.2 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 98.2 24.00 0 34 1 0
#> 95 24.00 0 68 0 1
#> 21.4 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 162 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.128 NA NA NA
#> 2 age, Cure model -0.00188 NA NA NA
#> 3 grade_ii, Cure model 0.405 NA NA NA
#> 4 grade_iii, Cure model 0.963 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00584 NA NA NA
#> 2 grade_ii, Survival model 0.200 NA NA NA
#> 3 grade_iii, Survival model 0.280 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.127774 -0.001876 0.404985 0.963421
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 255.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.127773711 -0.001875895 0.404985021 0.963420790
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00584286 0.19985152 0.27982460
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.58612790 0.38634413 0.56146630 0.28669509 0.51908368 0.70054120
#> [7] 0.79160308 0.36531943 0.40700519 0.83167325 0.61797157 0.42739076
#> [13] 0.09773588 0.41723827 0.92165620 0.81181709 0.90911672 0.75728983
#> [19] 0.49249767 0.67843434 0.38634413 0.07225836 0.13972207 0.74342703
#> [25] 0.69317953 0.65602705 0.61005955 0.64843463 0.61797157 0.33310342
#> [31] 0.28669509 0.75728983 0.86440313 0.13972207 0.79160308 0.54483197
#> [37] 0.20122634 0.84484815 0.86440313 0.67843434 0.20122634 0.97068443
#> [43] 0.95858000 0.70054120 0.03243881 0.93410527 0.84484815 0.74342703
#> [49] 0.58612790 0.94642199 0.56146630 0.64078179 0.53630801 0.97669407
#> [55] 0.90911672 0.54483197 0.48347330 0.57788746 0.88367836 0.65602705
#> [61] 0.43737704 0.27351163 0.94642199 0.97669407 0.79160308 0.85789758
#> [67] 0.71497776 0.67097957 0.43737704 0.61797157 0.25987890 0.93410527
#> [73] 0.77786502 0.72923412 0.51908368 0.75728983 0.11912940 0.97669407
#> [79] 0.73635522 0.51020232 0.97669407 0.71497776 0.33310342 0.77786502
#> [85] 0.46527881 0.81181709 0.83167325 0.46527881 0.90278997 0.86440313
#> [91] 0.96464151 0.60207703 0.43737704 0.81181709 0.49249767 0.23076159
#> [97] 0.28669509 0.18511999 0.89642820 0.88367836 0.36531943 0.32133976
#> [103] 0.92165620 0.24567680 0.13972207 0.33310342 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 110 150 40 99 108 167 123 128 158 177 181 170 92
#> 17.56 20.33 18.00 21.19 18.29 15.55 13.00 20.35 20.14 12.53 16.46 19.54 22.92
#> 166 187 140 101 81 179 6 150.1 164 63 13 39 100
#> 19.98 9.92 12.68 9.97 14.06 18.63 15.64 20.33 23.60 22.77 14.34 15.59 16.07
#> 171 79 181.1 190 99.1 81.1 10 63.1 123.1 41 169 49 10.1
#> 16.57 16.23 16.46 20.81 21.19 14.06 10.53 22.77 13.00 18.02 22.41 12.19 10.53
#> 6.1 169.1 91 77 167.1 24 183 49.1 13.1 110.1 16 40.1 192
#> 15.64 22.41 5.33 7.27 15.55 23.89 9.24 12.19 14.34 17.56 8.71 18.00 16.44
#> 51 127 101.1 41.1 97 184 52 100.1 55 153 16.1 127.1 123.2
#> 18.23 3.53 9.97 18.02 19.14 17.77 10.42 16.07 19.34 21.33 8.71 3.53 13.00
#> 43 18 26 55.1 181.2 139 183.1 155 96 108.1 81.2 113 127.2
#> 12.10 15.21 15.77 19.34 16.46 21.49 9.24 13.08 14.54 18.29 14.06 22.86 3.53
#> 57 88 127.3 18.1 190.1 155.1 76 140.1 177.1 76.1 145 10.2 25
#> 14.46 18.37 3.53 15.21 20.81 13.08 19.22 12.68 12.53 19.22 10.07 10.53 6.32
#> 23 58 140.2 179.1 66 36 15 93 52.1 128.1 32 187.1 197
#> 16.92 19.34 12.68 18.63 22.13 21.19 22.68 10.33 10.42 20.35 20.90 9.92 21.60
#> 63.2 190.2 54 34 185 126 31 161 109 148 193 82 21
#> 22.77 20.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 116 35 98 19 34.1 178 182 31.1 151 112 47 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 21.2 46 27 131 44 67 174 46.1 9 22 75 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 31.2 104 27.1 161.1 34.2 21.3 156 35.1 9.1 62 17 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 11 71.1 103 147 174.1 82.1 148.1 178.1 152 65 98.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 74 191 191.1 122 54.1 7 62.1 7.1 118 200 165 46.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 98.2 95 21.4 193.1 186 72 162 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[72]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01967761 0.78350788 0.87987155
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.255588911 -0.009169979 0.278818526
#> grade_iii, Cure model
#> 0.904514998
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 113 22.86 1 34 0 0
#> 97 19.14 1 65 0 1
#> 110 17.56 1 65 0 1
#> 25 6.32 1 34 1 0
#> 89 11.44 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 96 14.54 1 33 0 1
#> 107 11.18 1 54 1 0
#> 5 16.43 1 51 0 1
#> 24 23.89 1 38 0 0
#> 194 22.40 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 18 15.21 1 49 1 0
#> 127 3.53 1 62 0 1
#> 25.1 6.32 1 34 1 0
#> 15 22.68 1 48 0 0
#> 139 21.49 1 63 1 0
#> 60 13.15 1 38 1 0
#> 190 20.81 1 42 1 0
#> 57 14.46 1 45 0 1
#> 58.1 19.34 1 39 0 0
#> 68 20.62 1 44 0 0
#> 190.1 20.81 1 42 1 0
#> 40 18.00 1 28 1 0
#> 76 19.22 1 54 0 1
#> 40.1 18.00 1 28 1 0
#> 32 20.90 1 37 1 0
#> 56 12.21 1 60 0 0
#> 179 18.63 1 42 0 0
#> 78.1 23.88 1 43 0 0
#> 58.2 19.34 1 39 0 0
#> 18.1 15.21 1 49 1 0
#> 86 23.81 1 58 0 1
#> 99 21.19 1 38 0 1
#> 188 16.16 1 46 0 1
#> 42 12.43 1 49 0 1
#> 150 20.33 1 48 0 0
#> 149 8.37 1 33 1 0
#> 129 23.41 1 53 1 0
#> 66 22.13 1 53 0 0
#> 39 15.59 1 37 0 1
#> 88 18.37 1 47 0 0
#> 101 9.97 1 10 0 1
#> 127.1 3.53 1 62 0 1
#> 26 15.77 1 49 0 1
#> 5.1 16.43 1 51 0 1
#> 158 20.14 1 74 1 0
#> 154 12.63 1 20 1 0
#> 81 14.06 1 34 0 0
#> 90 20.94 1 50 0 1
#> 153 21.33 1 55 1 0
#> 153.1 21.33 1 55 1 0
#> 166 19.98 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 97.1 19.14 1 65 0 1
#> 26.1 15.77 1 49 0 1
#> 49 12.19 1 48 1 0
#> 14 12.89 1 21 0 0
#> 106 16.67 1 49 1 0
#> 194.1 22.40 1 38 0 1
#> 59 10.16 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 99.1 21.19 1 38 0 1
#> 68.1 20.62 1 44 0 0
#> 79 16.23 1 54 1 0
#> 13 14.34 1 54 0 1
#> 139.1 21.49 1 63 1 0
#> 70 7.38 1 30 1 0
#> 111 17.45 1 47 0 1
#> 16 8.71 1 71 0 1
#> 166.1 19.98 1 48 0 0
#> 155 13.08 1 26 0 0
#> 57.1 14.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 15.2 22.68 1 48 0 0
#> 159 10.55 1 50 0 1
#> 70.1 7.38 1 30 1 0
#> 136 21.83 1 43 0 1
#> 68.2 20.62 1 44 0 0
#> 59.1 10.16 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 91 5.33 1 61 0 1
#> 134 17.81 1 47 1 0
#> 181 16.46 1 45 0 1
#> 106.1 16.67 1 49 1 0
#> 15.3 22.68 1 48 0 0
#> 30.1 17.43 1 78 0 0
#> 164 23.60 1 76 0 1
#> 195 11.76 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 153.2 21.33 1 55 1 0
#> 96.1 14.54 1 33 0 1
#> 114 13.68 1 NA 0 0
#> 40.2 18.00 1 28 1 0
#> 13.1 14.34 1 54 0 1
#> 18.2 15.21 1 49 1 0
#> 155.1 13.08 1 26 0 0
#> 39.1 15.59 1 37 0 1
#> 29 15.45 1 68 1 0
#> 78.2 23.88 1 43 0 0
#> 187 9.92 1 39 1 0
#> 129.1 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 167 15.55 1 56 1 0
#> 59.2 10.16 1 NA 1 0
#> 13.2 14.34 1 54 0 1
#> 153.3 21.33 1 55 1 0
#> 5.2 16.43 1 51 0 1
#> 180 14.82 1 37 0 0
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 46 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#> 1 24.00 0 23 1 0
#> 174.1 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 82.1 24.00 0 34 0 0
#> 102 24.00 0 49 0 0
#> 182 24.00 0 35 0 0
#> 165.1 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 35 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 47 24.00 0 38 0 1
#> 71.1 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 21 24.00 0 47 0 0
#> 1.1 24.00 0 23 1 0
#> 21.1 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 131.1 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 20 24.00 0 46 1 0
#> 160 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 151 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 2 24.00 0 9 0 0
#> 137.1 24.00 0 45 1 0
#> 102.1 24.00 0 49 0 0
#> 161 24.00 0 45 0 0
#> 146.1 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 160.1 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 198.1 24.00 0 66 0 1
#> 196 24.00 0 19 0 0
#> 178 24.00 0 52 1 0
#> 116.1 24.00 0 58 0 1
#> 7 24.00 0 37 1 0
#> 163 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 144 24.00 0 28 0 1
#> 102.2 24.00 0 49 0 0
#> 172 24.00 0 41 0 0
#> 94.1 24.00 0 51 0 1
#> 65 24.00 0 57 1 0
#> 112.1 24.00 0 61 0 0
#> 198.2 24.00 0 66 0 1
#> 83 24.00 0 6 0 0
#> 72 24.00 0 40 0 1
#> 95.1 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 95.2 24.00 0 68 0 1
#> 112.2 24.00 0 61 0 0
#> 186.1 24.00 0 45 1 0
#> 54.1 24.00 0 53 1 0
#> 104 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 138 24.00 0 44 1 0
#> 20.2 24.00 0 46 1 0
#> 2.1 24.00 0 9 0 0
#> 151.1 24.00 0 42 0 0
#> 156.1 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 137.2 24.00 0 45 1 0
#> 98.1 24.00 0 34 1 0
#> 172.1 24.00 0 41 0 0
#> 104.1 24.00 0 50 1 0
#> 193.1 24.00 0 45 0 1
#> 156.2 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.256 NA NA NA
#> 2 age, Cure model -0.00917 NA NA NA
#> 3 grade_ii, Cure model 0.279 NA NA NA
#> 4 grade_iii, Cure model 0.905 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0197 NA NA NA
#> 2 grade_ii, Survival model 0.784 NA NA NA
#> 3 grade_iii, Survival model 0.880 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.25559 -0.00917 0.27882 0.90451
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 255.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.255588911 -0.009169979 0.278818526 0.904514998
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01967761 0.78350788 0.87987155
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2284067398 0.0228836953 0.2675688000 0.3504406606 0.9399844401
#> [6] 0.0013128785 0.6075745545 0.8187936029 0.4383991006 0.0001588145
#> [11] 0.0506108592 0.3717518363 0.5618469451 0.9758879226 0.9399844401
#> [16] 0.0278130213 0.0775735631 0.6995719357 0.1522598999 0.6304980717
#> [21] 0.2284067398 0.1676725025 0.1522598999 0.3093598158 0.2574373380
#> [26] 0.3093598158 0.1443831468 0.7706781805 0.2879468760 0.0013128785
#> [31] 0.2284067398 0.5618469451 0.0072149080 0.1212218155 0.4827751175
#> [36] 0.7587844426 0.1921645704 0.9039393371 0.0148344609 0.0632616466
#> [41] 0.5166502597 0.2985375069 0.8676600771 0.9758879226 0.4941261187
#> [46] 0.4383991006 0.2009406160 0.7469057664 0.6878152301 0.1364819367
#> [51] 0.0921456450 0.0921456450 0.2099084703 0.0278130213 0.2675688000
#> [56] 0.4941261187 0.7827004832 0.7349363103 0.3937467481 0.0506108592
#> [61] 0.7827004832 0.1212218155 0.1676725025 0.4714307913 0.6534263528
#> [66] 0.0775735631 0.9160524085 0.3610893230 0.8918029209 0.2099084703
#> [71] 0.7113214575 0.6304980717 0.8431479222 0.0278130213 0.8309619473
#> [76] 0.9160524085 0.0704297530 0.1676725025 0.8066691402 0.9638428397
#> [81] 0.3398974568 0.4159469353 0.3937467481 0.0278130213 0.3717518363
#> [86] 0.0107114629 0.4272009536 0.0921456450 0.6075745545 0.3093598158
#> [91] 0.6534263528 0.5618469451 0.7113214575 0.5166502597 0.5503804455
#> [96] 0.0013128785 0.8797328403 0.0148344609 0.8554204214 0.5390147479
#> [101] 0.6534263528 0.0921456450 0.4383991006 0.5958872377 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 58 113 97 110 25 78 96 107 5 24 194 30 18
#> 19.34 22.86 19.14 17.56 6.32 23.88 14.54 11.18 16.43 23.89 22.40 17.43 15.21
#> 127 25.1 15 139 60 190 57 58.1 68 190.1 40 76 40.1
#> 3.53 6.32 22.68 21.49 13.15 20.81 14.46 19.34 20.62 20.81 18.00 19.22 18.00
#> 32 56 179 78.1 58.2 18.1 86 99 188 42 150 149 129
#> 20.90 12.21 18.63 23.88 19.34 15.21 23.81 21.19 16.16 12.43 20.33 8.37 23.41
#> 66 39 88 101 127.1 26 5.1 158 154 81 90 153 153.1
#> 22.13 15.59 18.37 9.97 3.53 15.77 16.43 20.14 12.63 14.06 20.94 21.33 21.33
#> 166 15.1 97.1 26.1 49 14 106 194.1 49.1 99.1 68.1 79 13
#> 19.98 22.68 19.14 15.77 12.19 12.89 16.67 22.40 12.19 21.19 20.62 16.23 14.34
#> 139.1 70 111 16 166.1 155 57.1 10 15.2 159 70.1 136 68.2
#> 21.49 7.38 17.45 8.71 19.98 13.08 14.46 10.53 22.68 10.55 7.38 21.83 20.62
#> 43 91 134 181 106.1 15.3 30.1 164 192 153.2 96.1 40.2 13.1
#> 12.10 5.33 17.81 16.46 16.67 22.68 17.43 23.60 16.44 21.33 14.54 18.00 14.34
#> 18.2 155.1 39.1 29 78.2 187 129.1 61 167 13.2 153.3 5.2 180
#> 15.21 13.08 15.59 15.45 23.88 9.92 23.41 10.12 15.55 14.34 21.33 16.43 14.82
#> 186 116 71 137 94 46 74 82 174 1 174.1 165 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 62 98 82.1 102 182 165.1 112 35 48 47 71.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 1.1 21.1 191 131.1 200 20 160 146 185 54 151 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 19 2 137.1 102.1 161 146.1 34 160.1 11 198.1 196 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 7 163 95 193 144 102.2 172 94.1 65 112.1 198.2 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 95.1 27 95.2 112.2 186.1 54.1 104 20.1 138 20.2 2.1 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 80 137.2 98.1 172.1 104.1 193.1 156.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[73]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007263504 0.085386455 0.150946881
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86138743 0.01357015 0.19991219
#> grade_iii, Cure model
#> 1.00193075
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 49 12.19 1 48 1 0
#> 183 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 194 22.40 1 38 0 1
#> 26 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 177 12.53 1 75 0 0
#> 76 19.22 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 92 22.92 1 47 0 1
#> 60 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 70 7.38 1 30 1 0
#> 91 5.33 1 61 0 1
#> 6.1 15.64 1 39 0 0
#> 181 16.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 127 3.53 1 62 0 1
#> 90 20.94 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 57.1 14.46 1 45 0 1
#> 96 14.54 1 33 0 1
#> 145 10.07 1 65 1 0
#> 105 19.75 1 60 0 0
#> 58 19.34 1 39 0 0
#> 23 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 56 12.21 1 60 0 0
#> 29 15.45 1 68 1 0
#> 18 15.21 1 49 1 0
#> 190 20.81 1 42 1 0
#> 36 21.19 1 48 0 1
#> 39 15.59 1 37 0 1
#> 63 22.77 1 31 1 0
#> 57.2 14.46 1 45 0 1
#> 85.1 16.44 1 36 0 0
#> 37 12.52 1 57 1 0
#> 117 17.46 1 26 0 1
#> 63.1 22.77 1 31 1 0
#> 60.1 13.15 1 38 1 0
#> 42 12.43 1 49 0 1
#> 170 19.54 1 43 0 1
#> 23.1 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 43 12.10 1 61 0 1
#> 105.1 19.75 1 60 0 0
#> 100 16.07 1 60 0 0
#> 60.2 13.15 1 38 1 0
#> 58.1 19.34 1 39 0 0
#> 70.1 7.38 1 30 1 0
#> 139 21.49 1 63 1 0
#> 158 20.14 1 74 1 0
#> 108 18.29 1 39 0 1
#> 78 23.88 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 197.2 21.60 1 69 1 0
#> 43.1 12.10 1 61 0 1
#> 99.1 21.19 1 38 0 1
#> 56.1 12.21 1 60 0 0
#> 157 15.10 1 47 0 0
#> 51 18.23 1 83 0 1
#> 158.1 20.14 1 74 1 0
#> 89.1 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 111 17.45 1 47 0 1
#> 36.1 21.19 1 48 0 1
#> 110 17.56 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 149 8.37 1 33 1 0
#> 158.2 20.14 1 74 1 0
#> 140 12.68 1 59 1 0
#> 18.1 15.21 1 49 1 0
#> 10 10.53 1 34 0 0
#> 187 9.92 1 39 1 0
#> 130 16.47 1 53 0 1
#> 13 14.34 1 54 0 1
#> 136 21.83 1 43 0 1
#> 108.1 18.29 1 39 0 1
#> 108.2 18.29 1 39 0 1
#> 130.1 16.47 1 53 0 1
#> 51.1 18.23 1 83 0 1
#> 32 20.90 1 37 1 0
#> 97 19.14 1 65 0 1
#> 45 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 24.1 23.89 1 38 0 0
#> 195.1 11.76 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 16.1 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 129 23.41 1 53 1 0
#> 52 10.42 1 52 0 1
#> 92.1 22.92 1 47 0 1
#> 13.1 14.34 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 179 18.63 1 42 0 0
#> 91.1 5.33 1 61 0 1
#> 184 17.77 1 38 0 0
#> 187.1 9.92 1 39 1 0
#> 81 14.06 1 34 0 0
#> 134 17.81 1 47 1 0
#> 100.1 16.07 1 60 0 0
#> 41 18.02 1 40 1 0
#> 190.1 20.81 1 42 1 0
#> 99.2 21.19 1 38 0 1
#> 51.2 18.23 1 83 0 1
#> 194.1 22.40 1 38 0 1
#> 158.3 20.14 1 74 1 0
#> 74 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 185 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 54 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 22 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 44 24.00 0 56 0 0
#> 132 24.00 0 55 0 0
#> 151 24.00 0 42 0 0
#> 67 24.00 0 25 0 0
#> 11 24.00 0 42 0 1
#> 22.2 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 118.1 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 74.1 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 47 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 12 24.00 0 63 0 0
#> 178 24.00 0 52 1 0
#> 34 24.00 0 36 0 0
#> 144 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 132.1 24.00 0 55 0 0
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 71 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 34.1 24.00 0 36 0 0
#> 119 24.00 0 17 0 0
#> 118.2 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 71.1 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 80 24.00 0 41 0 0
#> 95.1 24.00 0 68 0 1
#> 71.2 24.00 0 51 0 0
#> 17.1 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 173 24.00 0 19 0 1
#> 103.1 24.00 0 56 1 0
#> 1 24.00 0 23 1 0
#> 176 24.00 0 43 0 1
#> 17.2 24.00 0 38 0 1
#> 34.2 24.00 0 36 0 0
#> 27 24.00 0 63 1 0
#> 144.1 24.00 0 28 0 1
#> 142 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 146.1 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 144.2 24.00 0 28 0 1
#> 185.1 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 72.1 24.00 0 40 0 1
#> 186 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 148.1 24.00 0 61 1 0
#> 48 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 148.2 24.00 0 61 1 0
#> 143 24.00 0 51 0 0
#> 22.3 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 142.1 24.00 0 53 0 0
#> 54.1 24.00 0 53 1 0
#> 62.1 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 121 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 178.1 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 22.4 24.00 0 52 1 0
#> 46 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.861 NA NA NA
#> 2 age, Cure model 0.0136 NA NA NA
#> 3 grade_ii, Cure model 0.200 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00726 NA NA NA
#> 2 grade_ii, Survival model 0.0854 NA NA NA
#> 3 grade_iii, Survival model 0.151 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86139 0.01357 0.19991 1.00193
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 254.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86138743 0.01357015 0.19991219 1.00193075
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007263504 0.085386455 0.150946881
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.71539579 0.88363196 0.93998381 0.25507237 0.20928443 0.70821223
#> [7] 0.43930487 0.85132311 0.49494173 0.25507237 0.14060918 0.81180711
#> [13] 0.67185680 0.97026231 0.98223225 0.71539579 0.66444325 0.77148795
#> [19] 0.83154067 0.99408501 0.35881530 0.77148795 0.76457146 0.92144506
#> [25] 0.44891872 0.47679074 0.62681898 0.30578791 0.87083795 0.73669760
#> [31] 0.74374403 0.38079756 0.30578791 0.72959787 0.17614942 0.77148795
#> [37] 0.67185680 0.85786018 0.60337344 0.17614942 0.81180711 0.86436514
#> [43] 0.46751042 0.62681898 0.64200877 0.89002704 0.44891872 0.69382211
#> [49] 0.81180711 0.47679074 0.97026231 0.29298063 0.40176211 0.52172958
#> [55] 0.09162013 0.25507237 0.89002704 0.30578791 0.87083795 0.75762493
#> [61] 0.54713195 0.40176211 0.90262491 0.61125489 0.30578791 0.59545011
#> [67] 0.04289898 0.96423233 0.40176211 0.83816256 0.74374403 0.90891637
#> [73] 0.92766299 0.64959797 0.79172165 0.23985606 0.52172958 0.52172958
#> [79] 0.64959797 0.54713195 0.36987581 0.50398130 0.61907222 0.68650604
#> [85] 0.04289898 0.95218122 0.95218122 0.84474948 0.11762541 0.91519565
#> [91] 0.14060918 0.79172165 0.93998381 0.51288282 0.98223225 0.58743457
#> [97] 0.92766299 0.80510371 0.57938410 0.69382211 0.57127366 0.38079756
#> [103] 0.30578791 0.54713195 0.20928443 0.40176211 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 6 49 183 197 194 26 166 177 76 197.1 92 60 85
#> 15.64 12.19 9.24 21.60 22.40 15.77 19.98 12.53 19.22 21.60 22.92 13.15 16.44
#> 70 91 6.1 181 57 14 127 90 57.1 96 145 105 58
#> 7.38 5.33 15.64 16.46 14.46 12.89 3.53 20.94 14.46 14.54 10.07 19.75 19.34
#> 23 99 56 29 18 190 36 39 63 57.2 85.1 37 117
#> 16.92 21.19 12.21 15.45 15.21 20.81 21.19 15.59 22.77 14.46 16.44 12.52 17.46
#> 63.1 60.1 42 170 23.1 171 43 105.1 100 60.2 58.1 70.1 139
#> 22.77 13.15 12.43 19.54 16.92 16.57 12.10 19.75 16.07 13.15 19.34 7.38 21.49
#> 158 108 78 197.2 43.1 99.1 56.1 157 51 158.1 159 111 36.1
#> 20.14 18.29 23.88 21.60 12.10 21.19 12.21 15.10 18.23 20.14 10.55 17.45 21.19
#> 110 24 149 158.2 140 18.1 10 187 130 13 136 108.1 108.2
#> 17.56 23.89 8.37 20.14 12.68 15.21 10.53 9.92 16.47 14.34 21.83 18.29 18.29
#> 130.1 51.1 32 97 45 79 24.1 16 16.1 154 129 52 92.1
#> 16.47 18.23 20.90 19.14 17.42 16.23 23.89 8.71 8.71 12.63 23.41 10.42 22.92
#> 13.1 183.1 179 91.1 184 187.1 81 134 100.1 41 190.1 99.2 51.2
#> 14.34 9.24 18.63 5.33 17.77 9.92 14.06 17.81 16.07 18.02 20.81 21.19 18.23
#> 194.1 158.3 74 87 185 112 54 131 200 22 22.1 44 132
#> 22.40 20.14 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 67 11 22.2 95 118 33 162 72 118.1 193 146 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 47 62 174 12 178 34 144 17 132.1 147 147.1 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 119 118.2 148 71.1 7 80 95.1 71.2 17.1 137 173 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 176 17.2 34.2 27 144.1 142 198 146.1 182 144.2 185.1 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 186 102 148.1 48 19 148.2 143 22.3 161 3 142.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 152 121 83 178.1 109 121.1 98 22.4 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[74]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005846302 0.250317686 0.513368906
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.769705122 0.005133718 0.662222009
#> grade_iii, Cure model
#> 1.513526488
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 14 12.89 1 21 0 0
#> 36 21.19 1 48 0 1
#> 129 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 171 16.57 1 41 0 1
#> 89 11.44 1 NA 0 0
#> 49 12.19 1 48 1 0
#> 110 17.56 1 65 0 1
#> 89.1 11.44 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 117 17.46 1 26 0 1
#> 43 12.10 1 61 0 1
#> 184 17.77 1 38 0 0
#> 58 19.34 1 39 0 0
#> 145 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 164.1 23.60 1 76 0 1
#> 140 12.68 1 59 1 0
#> 127.1 3.53 1 62 0 1
#> 167 15.55 1 56 1 0
#> 129.1 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 4 17.64 1 NA 0 1
#> 139 21.49 1 63 1 0
#> 171.1 16.57 1 41 0 1
#> 89.2 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 55 19.34 1 69 0 1
#> 127.2 3.53 1 62 0 1
#> 133 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 50 10.02 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 154 12.63 1 20 1 0
#> 16.1 8.71 1 71 0 1
#> 86 23.81 1 58 0 1
#> 190 20.81 1 42 1 0
#> 42.1 12.43 1 49 0 1
#> 29 15.45 1 68 1 0
#> 153 21.33 1 55 1 0
#> 124 9.73 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 93 10.33 1 52 0 1
#> 169 22.41 1 46 0 0
#> 45 17.42 1 54 0 1
#> 117.1 17.46 1 26 0 1
#> 58.1 19.34 1 39 0 0
#> 140.1 12.68 1 59 1 0
#> 100 16.07 1 60 0 0
#> 76 19.22 1 54 0 1
#> 127.3 3.53 1 62 0 1
#> 36.1 21.19 1 48 0 1
#> 129.2 23.41 1 53 1 0
#> 123 13.00 1 44 1 0
#> 128 20.35 1 35 0 1
#> 15 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 101 9.97 1 10 0 1
#> 117.2 17.46 1 26 0 1
#> 58.2 19.34 1 39 0 0
#> 60 13.15 1 38 1 0
#> 78 23.88 1 43 0 0
#> 108 18.29 1 39 0 1
#> 117.3 17.46 1 26 0 1
#> 76.1 19.22 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 63 22.77 1 31 1 0
#> 10 10.53 1 34 0 0
#> 18 15.21 1 49 1 0
#> 61.1 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 145.1 10.07 1 65 1 0
#> 129.3 23.41 1 53 1 0
#> 179 18.63 1 42 0 0
#> 79 16.23 1 54 1 0
#> 110.1 17.56 1 65 0 1
#> 129.4 23.41 1 53 1 0
#> 111 17.45 1 47 0 1
#> 68 20.62 1 44 0 0
#> 175 21.91 1 43 0 0
#> 85 16.44 1 36 0 0
#> 179.1 18.63 1 42 0 0
#> 78.1 23.88 1 43 0 0
#> 63.1 22.77 1 31 1 0
#> 171.2 16.57 1 41 0 1
#> 100.1 16.07 1 60 0 0
#> 93.1 10.33 1 52 0 1
#> 23.1 16.92 1 61 0 0
#> 59 10.16 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 124.1 9.73 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 45.1 17.42 1 54 0 1
#> 181.1 16.46 1 45 0 1
#> 183 9.24 1 67 1 0
#> 140.2 12.68 1 59 1 0
#> 90 20.94 1 50 0 1
#> 76.2 19.22 1 54 0 1
#> 61.2 10.12 1 36 0 1
#> 180 14.82 1 37 0 0
#> 32 20.90 1 37 1 0
#> 99 21.19 1 38 0 1
#> 18.1 15.21 1 49 1 0
#> 18.2 15.21 1 49 1 0
#> 153.1 21.33 1 55 1 0
#> 192 16.44 1 31 1 0
#> 69 23.23 1 25 0 1
#> 153.2 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 134.1 17.81 1 47 1 0
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 118 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 72 24.00 0 40 0 1
#> 33.1 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 135 24.00 0 58 1 0
#> 121 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 94 24.00 0 51 0 1
#> 74 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 165.1 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 12.1 24.00 0 63 0 0
#> 142 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 131 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 161.1 24.00 0 45 0 0
#> 3 24.00 0 31 1 0
#> 165.2 24.00 0 47 0 0
#> 132 24.00 0 55 0 0
#> 33.2 24.00 0 53 0 0
#> 186.2 24.00 0 45 1 0
#> 72.1 24.00 0 40 0 1
#> 141 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 104 24.00 0 50 1 0
#> 21 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 53.1 24.00 0 32 0 1
#> 146 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 162 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 19.2 24.00 0 57 0 1
#> 112 24.00 0 61 0 0
#> 48 24.00 0 31 1 0
#> 19.3 24.00 0 57 0 1
#> 1 24.00 0 23 1 0
#> 137 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 75 24.00 0 21 1 0
#> 54 24.00 0 53 1 0
#> 95 24.00 0 68 0 1
#> 118.1 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 33.3 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 80 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 19.4 24.00 0 57 0 1
#> 48.1 24.00 0 31 1 0
#> 142.1 24.00 0 53 0 0
#> 46.1 24.00 0 71 0 0
#> 95.1 24.00 0 68 0 1
#> 3.1 24.00 0 31 1 0
#> 19.5 24.00 0 57 0 1
#> 174 24.00 0 49 1 0
#> 143 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 176.1 24.00 0 43 0 1
#> 67.1 24.00 0 25 0 0
#> 82.1 24.00 0 34 0 0
#> 82.2 24.00 0 34 0 0
#> 82.3 24.00 0 34 0 0
#> 138.1 24.00 0 44 1 0
#> 165.3 24.00 0 47 0 0
#> 9.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.770 NA NA NA
#> 2 age, Cure model 0.00513 NA NA NA
#> 3 grade_ii, Cure model 0.662 NA NA NA
#> 4 grade_iii, Cure model 1.51 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00585 NA NA NA
#> 2 grade_ii, Survival model 0.250 NA NA NA
#> 3 grade_iii, Survival model 0.513 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.769705 0.005134 0.662222 1.513526
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 244.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.769705122 0.005133718 0.662222009 1.513526488
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005846302 0.250317686 0.513368906
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.768048830 0.229182479 0.063222895 0.041995769 0.543393996 0.833927410
#> [7] 0.438508663 0.815177486 0.645928631 0.458374153 0.843358854 0.428394760
#> [13] 0.309860653 0.908415249 0.963803130 0.041995769 0.777522894 0.963803130
#> [19] 0.655310033 0.063222895 0.880871719 0.187614079 0.543393996 0.749128485
#> [25] 0.309860653 0.963803130 0.711431529 0.720910152 0.945418046 0.805692103
#> [31] 0.945418046 0.029176984 0.279263436 0.815177486 0.664701410 0.198350478
#> [37] 0.571286553 0.862204784 0.156474139 0.505462993 0.458374153 0.309860653
#> [43] 0.777522894 0.627208734 0.349093620 0.963803130 0.229182479 0.063222895
#> [49] 0.758588250 0.299718014 0.146225140 0.524325583 0.926917402 0.458374153
#> [55] 0.309860653 0.730361618 0.008065272 0.398437840 0.458374153 0.349093620
#> [61] 0.408498210 0.126767490 0.852772434 0.674110990 0.880871719 0.617861071
#> [67] 0.908415249 0.063222895 0.378406257 0.608474087 0.438508663 0.063222895
#> [73] 0.495863031 0.289449729 0.166884111 0.589862967 0.378406257 0.008065272
#> [79] 0.126767490 0.543393996 0.627208734 0.862204784 0.524325583 0.730361618
#> [85] 0.166884111 0.505462993 0.571286553 0.936161698 0.777522894 0.258874063
#> [91] 0.349093620 0.880871719 0.701988563 0.269075406 0.229182479 0.674110990
#> [97] 0.674110990 0.198350478 0.589862967 0.106432380 0.198350478 0.116519741
#> [103] 0.408498210 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 14 36 129 164 171 49 110 42 39 117 43 184 58
#> 12.89 21.19 23.41 23.60 16.57 12.19 17.56 12.43 15.59 17.46 12.10 17.77 19.34
#> 145 127 164.1 140 127.1 167 129.1 61 139 171.1 155 55 127.2
#> 10.07 3.53 23.60 12.68 3.53 15.55 23.41 10.12 21.49 16.57 13.08 19.34 3.53
#> 133 13 16 154 16.1 86 190 42.1 29 153 181 93 169
#> 14.65 14.34 8.71 12.63 8.71 23.81 20.81 12.43 15.45 21.33 16.46 10.33 22.41
#> 45 117.1 58.1 140.1 100 76 127.3 36.1 129.2 123 128 15 23
#> 17.42 17.46 19.34 12.68 16.07 19.22 3.53 21.19 23.41 13.00 20.35 22.68 16.92
#> 101 117.2 58.2 60 78 108 117.3 76.1 134 63 10 18 61.1
#> 9.97 17.46 19.34 13.15 23.88 18.29 17.46 19.22 17.81 22.77 10.53 15.21 10.12
#> 188 145.1 129.3 179 79 110.1 129.4 111 68 175 85 179.1 78.1
#> 16.16 10.07 23.41 18.63 16.23 17.56 23.41 17.45 20.62 21.91 16.44 18.63 23.88
#> 63.1 171.2 100.1 93.1 23.1 60.1 175.1 45.1 181.1 183 140.2 90 76.2
#> 22.77 16.57 16.07 10.33 16.92 13.15 21.91 17.42 16.46 9.24 12.68 20.94 19.22
#> 61.2 180 32 99 18.1 18.2 153.1 192 69 153.2 113 134.1 186
#> 10.12 14.82 20.90 21.19 15.21 15.21 21.33 16.44 23.23 21.33 22.86 17.81 24.00
#> 82 118 33 34 87 156 72 33.1 161 135 121 9 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 186.1 27 35 12 94 74 44 46 165.1 62 67 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 151 131 151.1 53 161.1 3 165.2 132 33.2 186.2 72.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 104 21 22 53.1 146 64 162 38 19.1 7 19.2 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 19.3 1 137 2 75 54 95 118.1 44.1 33.3 138 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 196 19.4 48.1 142.1 46.1 95.1 3.1 19.5 174 143 176 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 67.1 82.1 82.2 82.3 138.1 165.3 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[75]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00856789 0.68063581 0.32866374
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.069679742 -0.004526986 0.326147058
#> grade_iii, Cure model
#> 0.857971849
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 117 17.46 1 26 0 1
#> 60 13.15 1 38 1 0
#> 79 16.23 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 113 22.86 1 34 0 0
#> 150 20.33 1 48 0 0
#> 41 18.02 1 40 1 0
#> 42 12.43 1 49 0 1
#> 180 14.82 1 37 0 0
#> 194 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 37 12.52 1 57 1 0
#> 14 12.89 1 21 0 0
#> 30 17.43 1 78 0 0
#> 130.1 16.47 1 53 0 1
#> 69 23.23 1 25 0 1
#> 43 12.10 1 61 0 1
#> 101 9.97 1 10 0 1
#> 25 6.32 1 34 1 0
#> 25.1 6.32 1 34 1 0
#> 113.1 22.86 1 34 0 0
#> 55 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 149 8.37 1 33 1 0
#> 168 23.72 1 70 0 0
#> 189.1 10.51 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 18 15.21 1 49 1 0
#> 188 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 108 18.29 1 39 0 1
#> 85 16.44 1 36 0 0
#> 134 17.81 1 47 1 0
#> 14.1 12.89 1 21 0 0
#> 23 16.92 1 61 0 0
#> 179 18.63 1 42 0 0
#> 37.1 12.52 1 57 1 0
#> 43.1 12.10 1 61 0 1
#> 59.1 10.16 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 150.1 20.33 1 48 0 0
#> 14.2 12.89 1 21 0 0
#> 43.2 12.10 1 61 0 1
#> 140 12.68 1 59 1 0
#> 171.1 16.57 1 41 0 1
#> 127 3.53 1 62 0 1
#> 29 15.45 1 68 1 0
#> 50 10.02 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 150.2 20.33 1 48 0 0
#> 125 15.65 1 67 1 0
#> 15 22.68 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 26 15.77 1 49 0 1
#> 177 12.53 1 75 0 0
#> 128 20.35 1 35 0 1
#> 117.1 17.46 1 26 0 1
#> 106 16.67 1 49 1 0
#> 78 23.88 1 43 0 0
#> 29.1 15.45 1 68 1 0
#> 40.1 18.00 1 28 1 0
#> 181 16.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 117.2 17.46 1 26 0 1
#> 181.1 16.46 1 45 0 1
#> 76.1 19.22 1 54 0 1
#> 68 20.62 1 44 0 0
#> 177.1 12.53 1 75 0 0
#> 5 16.43 1 51 0 1
#> 158.1 20.14 1 74 1 0
#> 130.2 16.47 1 53 0 1
#> 60.1 13.15 1 38 1 0
#> 107 11.18 1 54 1 0
#> 79.1 16.23 1 54 1 0
#> 40.2 18.00 1 28 1 0
#> 78.1 23.88 1 43 0 0
#> 57 14.46 1 45 0 1
#> 56.1 12.21 1 60 0 0
#> 128.1 20.35 1 35 0 1
#> 127.1 3.53 1 62 0 1
#> 90 20.94 1 50 0 1
#> 100 16.07 1 60 0 0
#> 69.1 23.23 1 25 0 1
#> 77 7.27 1 67 0 1
#> 85.1 16.44 1 36 0 0
#> 179.1 18.63 1 42 0 0
#> 42.1 12.43 1 49 0 1
#> 136 21.83 1 43 0 1
#> 97 19.14 1 65 0 1
#> 177.2 12.53 1 75 0 0
#> 170.1 19.54 1 43 0 1
#> 169 22.41 1 46 0 0
#> 101.1 9.97 1 10 0 1
#> 68.1 20.62 1 44 0 0
#> 129 23.41 1 53 1 0
#> 154 12.63 1 20 1 0
#> 92.1 22.92 1 47 0 1
#> 85.2 16.44 1 36 0 0
#> 63 22.77 1 31 1 0
#> 41.1 18.02 1 40 1 0
#> 183.1 9.24 1 67 1 0
#> 93 10.33 1 52 0 1
#> 110 17.56 1 65 0 1
#> 37.2 12.52 1 57 1 0
#> 178 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 163 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 185 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 46 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 143 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 62 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 122.1 24.00 0 66 0 0
#> 53.1 24.00 0 32 0 1
#> 115.1 24.00 0 NA 1 0
#> 27 24.00 0 63 1 0
#> 73 24.00 0 NA 0 1
#> 31 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 1.1 24.00 0 23 1 0
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 109.1 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 178.1 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 64.1 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 31.1 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 172 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 22 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 178.2 24.00 0 52 1 0
#> 115.2 24.00 0 NA 1 0
#> 186 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 87.1 24.00 0 27 0 0
#> 131.1 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 109.2 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 118 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 72.1 24.00 0 40 0 1
#> 19.1 24.00 0 57 0 1
#> 165 24.00 0 47 0 0
#> 98 24.00 0 34 1 0
#> 193 24.00 0 45 0 1
#> 84 24.00 0 39 0 1
#> 198 24.00 0 66 0 1
#> 73.1 24.00 0 NA 0 1
#> 19.2 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 95.1 24.00 0 68 0 1
#> 178.3 24.00 0 52 1 0
#> 146.1 24.00 0 63 1 0
#> 31.2 24.00 0 36 0 1
#> 174 24.00 0 49 1 0
#> 94 24.00 0 51 0 1
#> 126 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 143.1 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 118.1 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 131.2 24.00 0 66 0 0
#> 118.2 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 11.1 24.00 0 42 0 1
#> 119.1 24.00 0 17 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0697 NA NA NA
#> 2 age, Cure model -0.00453 NA NA NA
#> 3 grade_ii, Cure model 0.326 NA NA NA
#> 4 grade_iii, Cure model 0.858 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00857 NA NA NA
#> 2 grade_ii, Survival model 0.681 NA NA NA
#> 3 grade_iii, Survival model 0.329 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.069680 -0.004527 0.326147 0.857972
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258
#> Residual Deviance: 251.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.069679742 -0.004526986 0.326147058 0.857971849
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00856789 0.68063581 0.32866374
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.61328799 0.70715395 0.65101633 0.84011904 0.76496707 0.54447243
#> [7] 0.83461126 0.28166682 0.45129866 0.59706633 0.90761751 0.81801106
#> [13] 0.36030575 0.92713977 0.89278537 0.85085503 0.67242311 0.70715395
#> [19] 0.20715822 0.93196545 0.95540179 0.98258726 0.98258726 0.28166682
#> [25] 0.52582813 0.91741354 0.96463327 0.97364848 0.14744489 0.24740527
#> [31] 0.81242380 0.77716008 0.81801106 0.58848104 0.73959307 0.63610092
#> [37] 0.85085503 0.67956297 0.57120040 0.89278537 0.93196545 0.69359664
#> [43] 0.45129866 0.85085503 0.93196545 0.86684863 0.69359664 0.99134573
#> [49] 0.80113249 0.48562817 0.45129866 0.79525595 0.33017195 0.52582813
#> [55] 0.78926849 0.87738560 0.42716694 0.65101633 0.68665170 0.07381983
#> [61] 0.80113249 0.61328799 0.72672701 0.50613015 0.65101633 0.72672701
#> [67] 0.54447243 0.40178133 0.87738560 0.75862932 0.48562817 0.70715395
#> [73] 0.84011904 0.94607493 0.76496707 0.61328799 0.07381983 0.82909116
#> [79] 0.91741354 0.42716694 0.99134573 0.38849099 0.78323001 0.20715822
#> [85] 0.97813284 0.73959307 0.57120040 0.90761751 0.37466534 0.56237725
#> [91] 0.87738560 0.50613015 0.34539750 0.95540179 0.40178133 0.18229991
#> [97] 0.87213851 0.24740527 0.73959307 0.31458083 0.59706633 0.96463327
#> [103] 0.95075173 0.64362017 0.89278537 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 40 130 117 60 79 76 81 113 150 41 42 180 194
#> 18.00 16.47 17.46 13.15 16.23 19.22 14.06 22.86 20.33 18.02 12.43 14.82 22.40
#> 49 37 14 30 130.1 69 43 101 25 25.1 113.1 55 56
#> 12.19 12.52 12.89 17.43 16.47 23.23 12.10 9.97 6.32 6.32 22.86 19.34 12.21
#> 183 149 168 92 18 188 180.1 108 85 134 14.1 23 179
#> 9.24 8.37 23.72 22.92 15.21 16.16 14.82 18.29 16.44 17.81 12.89 16.92 18.63
#> 37.1 43.1 171 150.1 14.2 43.2 140 171.1 127 29 158 150.2 125
#> 12.52 12.10 16.57 20.33 12.89 12.10 12.68 16.57 3.53 15.45 20.14 20.33 15.65
#> 15 55.1 26 177 128 117.1 106 78 29.1 40.1 181 170 117.2
#> 22.68 19.34 15.77 12.53 20.35 17.46 16.67 23.88 15.45 18.00 16.46 19.54 17.46
#> 181.1 76.1 68 177.1 5 158.1 130.2 60.1 107 79.1 40.2 78.1 57
#> 16.46 19.22 20.62 12.53 16.43 20.14 16.47 13.15 11.18 16.23 18.00 23.88 14.46
#> 56.1 128.1 127.1 90 100 69.1 77 85.1 179.1 42.1 136 97 177.2
#> 12.21 20.35 3.53 20.94 16.07 23.23 7.27 16.44 18.63 12.43 21.83 19.14 12.53
#> 170.1 169 101.1 68.1 129 154 92.1 85.2 63 41.1 183.1 93 110
#> 19.54 22.41 9.97 20.62 23.41 12.63 22.92 16.44 22.77 18.02 9.24 10.33 17.56
#> 37.2 178 162 163 11 185 7 46 122 95 1 151 53
#> 12.52 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 132 62 146 120 144 138 162.1 33 64 122.1 53.1 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 109 1.1 161 19 109.1 87 178.1 28 64.1 72 31.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 196 22 54 178.2 186 131 34 87.1 131.1 12 109.2 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 121 176 72.1 19.1 165 98 193 84 198 19.2 142 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 95.1 178.3 146.1 31.2 174 94 126 112 143.1 132.1 118.1 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.2 118.2 65 80 11.1 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[76]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004650114 0.632374730 0.726815356
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.87125727 0.01594684 -0.26957385
#> grade_iii, Cure model
#> 1.04312948
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 43 12.10 1 61 0 1
#> 180 14.82 1 37 0 0
#> 43.1 12.10 1 61 0 1
#> 188 16.16 1 46 0 1
#> 59 10.16 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 36 21.19 1 48 0 1
#> 153 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 168 23.72 1 70 0 0
#> 105 19.75 1 60 0 0
#> 190 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 76 19.22 1 54 0 1
#> 61 10.12 1 36 0 1
#> 6.1 15.64 1 39 0 0
#> 164 23.60 1 76 0 1
#> 127 3.53 1 62 0 1
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 177 12.53 1 75 0 0
#> 69 23.23 1 25 0 1
#> 43.2 12.10 1 61 0 1
#> 30 17.43 1 78 0 0
#> 25 6.32 1 34 1 0
#> 52 10.42 1 52 0 1
#> 39 15.59 1 37 0 1
#> 36.1 21.19 1 48 0 1
#> 5 16.43 1 51 0 1
#> 32 20.90 1 37 1 0
#> 59.1 10.16 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 77 7.27 1 67 0 1
#> 52.1 10.42 1 52 0 1
#> 127.1 3.53 1 62 0 1
#> 76.2 19.22 1 54 0 1
#> 181 16.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 52.2 10.42 1 52 0 1
#> 154 12.63 1 20 1 0
#> 4 17.64 1 NA 0 1
#> 197.1 21.60 1 69 1 0
#> 78 23.88 1 43 0 0
#> 184 17.77 1 38 0 0
#> 190.1 20.81 1 42 1 0
#> 43.3 12.10 1 61 0 1
#> 86 23.81 1 58 0 1
#> 23 16.92 1 61 0 0
#> 79 16.23 1 54 1 0
#> 105.1 19.75 1 60 0 0
#> 101 9.97 1 10 0 1
#> 79.1 16.23 1 54 1 0
#> 77.1 7.27 1 67 0 1
#> 26 15.77 1 49 0 1
#> 168.1 23.72 1 70 0 0
#> 189.1 10.51 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 69.1 23.23 1 25 0 1
#> 195 11.76 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 175 21.91 1 43 0 0
#> 59.2 10.16 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 29 15.45 1 68 1 0
#> 60 13.15 1 38 1 0
#> 189.2 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 68 20.62 1 44 0 0
#> 10 10.53 1 34 0 0
#> 6.2 15.64 1 39 0 0
#> 76.3 19.22 1 54 0 1
#> 42.1 12.43 1 49 0 1
#> 159 10.55 1 50 0 1
#> 43.4 12.10 1 61 0 1
#> 113 22.86 1 34 0 0
#> 41 18.02 1 40 1 0
#> 170 19.54 1 43 0 1
#> 195.1 11.76 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 58 19.34 1 39 0 0
#> 45 17.42 1 54 0 1
#> 194 22.40 1 38 0 1
#> 15.1 22.68 1 48 0 0
#> 88 18.37 1 47 0 0
#> 13 14.34 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 18 15.21 1 49 1 0
#> 92 22.92 1 47 0 1
#> 153.1 21.33 1 55 1 0
#> 61.1 10.12 1 36 0 1
#> 81 14.06 1 34 0 0
#> 66 22.13 1 53 0 0
#> 184.1 17.77 1 38 0 0
#> 167 15.55 1 56 1 0
#> 13.2 14.34 1 54 0 1
#> 18.1 15.21 1 49 1 0
#> 66.1 22.13 1 53 0 0
#> 96 14.54 1 33 0 1
#> 92.1 22.92 1 47 0 1
#> 68.1 20.62 1 44 0 0
#> 93 10.33 1 52 0 1
#> 78.1 23.88 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 69.2 23.23 1 25 0 1
#> 51 18.23 1 83 0 1
#> 58.1 19.34 1 39 0 0
#> 60.1 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 32.1 20.90 1 37 1 0
#> 169.1 22.41 1 46 0 0
#> 129 23.41 1 53 1 0
#> 87 24.00 0 27 0 0
#> 102 24.00 0 49 0 0
#> 126 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 17 24.00 0 38 0 1
#> 152 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 104 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 118 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 142 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 147 24.00 0 76 1 0
#> 73 24.00 0 NA 0 1
#> 17.1 24.00 0 38 0 1
#> 102.1 24.00 0 49 0 0
#> 44 24.00 0 56 0 0
#> 80 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 121 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 104.1 24.00 0 50 1 0
#> 87.1 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 147.1 24.00 0 76 1 0
#> 71 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 7 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 73.1 24.00 0 NA 0 1
#> 163 24.00 0 66 0 0
#> 121.1 24.00 0 57 1 0
#> 172.1 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 173.1 24.00 0 19 0 1
#> 54 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 83 24.00 0 6 0 0
#> 112 24.00 0 61 0 0
#> 54.1 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 72 24.00 0 40 0 1
#> 142.1 24.00 0 53 0 0
#> 122.1 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 67.1 24.00 0 25 0 0
#> 94 24.00 0 51 0 1
#> 9 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 73.2 24.00 0 NA 0 1
#> 17.2 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 72.1 24.00 0 40 0 1
#> 198 24.00 0 66 0 1
#> 67.2 24.00 0 25 0 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 121.2 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 132 24.00 0 55 0 0
#> 162.1 24.00 0 51 0 0
#> 102.2 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 44.1 24.00 0 56 0 0
#> 120 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 7.1 24.00 0 37 1 0
#> 31 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 137 24.00 0 45 1 0
#> 185.1 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 156.1 24.00 0 50 1 0
#> 21 24.00 0 47 0 0
#> 162.2 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.871 NA NA NA
#> 2 age, Cure model 0.0159 NA NA NA
#> 3 grade_ii, Cure model -0.270 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00465 NA NA NA
#> 2 grade_ii, Survival model 0.632 NA NA NA
#> 3 grade_iii, Survival model 0.727 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87126 0.01595 -0.26957 1.04313
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 241.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87125727 0.01594684 -0.26957385 1.04312948
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004650114 0.632374730 0.726815356
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.89640682 0.82197683 0.89640682 0.75871191 0.98612393 0.51162755
#> [7] 0.49117834 0.88546119 0.19926533 0.58443225 0.54926511 0.77176144
#> [13] 0.62722652 0.95243991 0.77176144 0.24815983 0.99080752 0.72464097
#> [19] 0.62722652 0.87986039 0.28890959 0.89640682 0.69551752 0.98140115
#> [25] 0.93247974 0.79094439 0.51162755 0.73861877 0.53085814 0.71748588
#> [31] 0.97192353 0.93247974 0.99080752 0.62722652 0.73168160 0.46943442
#> [37] 0.93247974 0.87424468 0.46943442 0.09819638 0.68069592 0.54926511
#> [43] 0.89640682 0.17020921 0.71022191 0.74545183 0.58443225 0.96708684
#> [49] 0.74545183 0.97192353 0.76528112 0.19926533 0.28890959 0.04247611
#> [55] 0.45754545 0.86859027 0.80361396 0.85720923 0.37141000 0.56691057
#> [61] 0.92732241 0.77176144 0.62722652 0.88546119 0.92216017 0.89640682
#> [67] 0.35826739 0.67321268 0.60178655 0.39678980 0.61033761 0.70293349
#> [73] 0.42178889 0.37141000 0.65785142 0.83408410 0.83408410 0.80983532
#> [79] 0.33230432 0.49117834 0.95243991 0.85140335 0.43394252 0.68069592
#> [85] 0.79731546 0.83408410 0.80983532 0.43394252 0.82806170 0.33230432
#> [91] 0.56691057 0.94746228 0.09819638 0.28890959 0.66562256 0.61033761
#> [97] 0.85720923 0.96222176 0.53085814 0.39678980 0.26961482 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 43 180 43.1 188 91 36 153 42 168 105 190 6 76
#> 12.10 14.82 12.10 16.16 5.33 21.19 21.33 12.43 23.72 19.75 20.81 15.64 19.22
#> 61 6.1 164 127 130 76.1 177 69 43.2 30 25 52 39
#> 10.12 15.64 23.60 3.53 16.47 19.22 12.53 23.23 12.10 17.43 6.32 10.42 15.59
#> 36.1 5 32 171 77 52.1 127.1 76.2 181 197 52.2 154 197.1
#> 21.19 16.43 20.90 16.57 7.27 10.42 3.53 19.22 16.46 21.60 10.42 12.63 21.60
#> 78 184 190.1 43.3 86 23 79 105.1 101 79.1 77.1 26 168.1
#> 23.88 17.77 20.81 12.10 23.81 16.92 16.23 19.75 9.97 16.23 7.27 15.77 23.72
#> 69.1 24 175 140 29 60 15 68 10 6.2 76.3 42.1 159
#> 23.23 23.89 21.91 12.68 15.45 13.15 22.68 20.62 10.53 15.64 19.22 12.43 10.55
#> 43.4 113 41 170 169 58 45 194 15.1 88 13 13.1 18
#> 12.10 22.86 18.02 19.54 22.41 19.34 17.42 22.40 22.68 18.37 14.34 14.34 15.21
#> 92 153.1 61.1 81 66 184.1 167 13.2 18.1 66.1 96 92.1 68.1
#> 22.92 21.33 10.12 14.06 22.13 17.77 15.55 14.34 15.21 22.13 14.54 22.92 20.62
#> 93 78.1 69.2 51 58.1 60.1 145 32.1 169.1 129 87 102 126
#> 10.33 23.88 23.23 18.23 19.34 13.15 10.07 20.90 22.41 23.41 24.00 24.00 24.00
#> 67 17 152 48 172 104 103 118 103.1 142 28 147 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 44 80 131 193 121 176 162 185 80.1 116 104.1 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 147.1 71 82 7 47 163 121.1 172.1 173 173.1 54 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 46 135 83 112 54.1 122 160 11.1 72 142.1 122.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 94 9 83.1 17.2 12 72.1 198 67.2 156 27 121.2 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 162.1 102.2 146 44.1 120 109 7.1 31 75 137 185.1 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 21 162.2 74
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[77]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007349469 0.405182053 0.429613096
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.38338316 0.00760682 0.12880101
#> grade_iii, Cure model
#> 0.61404223
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 117 17.46 1 26 0 1
#> 105 19.75 1 60 0 0
#> 85 16.44 1 36 0 0
#> 155.1 13.08 1 26 0 0
#> 175 21.91 1 43 0 0
#> 155.2 13.08 1 26 0 0
#> 78 23.88 1 43 0 0
#> 154 12.63 1 20 1 0
#> 100 16.07 1 60 0 0
#> 39 15.59 1 37 0 1
#> 107 11.18 1 54 1 0
#> 5 16.43 1 51 0 1
#> 97 19.14 1 65 0 1
#> 168 23.72 1 70 0 0
#> 140 12.68 1 59 1 0
#> 91 5.33 1 61 0 1
#> 106 16.67 1 49 1 0
#> 145 10.07 1 65 1 0
#> 124 9.73 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 60 13.15 1 38 1 0
#> 45 17.42 1 54 0 1
#> 41 18.02 1 40 1 0
#> 96 14.54 1 33 0 1
#> 90 20.94 1 50 0 1
#> 154.1 12.63 1 20 1 0
#> 127 3.53 1 62 0 1
#> 30 17.43 1 78 0 0
#> 105.1 19.75 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 171 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 41.1 18.02 1 40 1 0
#> 78.1 23.88 1 43 0 0
#> 55 19.34 1 69 0 1
#> 150 20.33 1 48 0 0
#> 134 17.81 1 47 1 0
#> 26 15.77 1 49 0 1
#> 145.1 10.07 1 65 1 0
#> 69 23.23 1 25 0 1
#> 39.1 15.59 1 37 0 1
#> 18 15.21 1 49 1 0
#> 110 17.56 1 65 0 1
#> 78.2 23.88 1 43 0 0
#> 16 8.71 1 71 0 1
#> 4 17.64 1 NA 0 1
#> 127.1 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 23 16.92 1 61 0 0
#> 30.1 17.43 1 78 0 0
#> 164 23.60 1 76 0 1
#> 85.1 16.44 1 36 0 0
#> 13 14.34 1 54 0 1
#> 155.3 13.08 1 26 0 0
#> 164.1 23.60 1 76 0 1
#> 25 6.32 1 34 1 0
#> 107.1 11.18 1 54 1 0
#> 133 14.65 1 57 0 0
#> 171.1 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 157 15.10 1 47 0 0
#> 52 10.42 1 52 0 1
#> 110.1 17.56 1 65 0 1
#> 139 21.49 1 63 1 0
#> 85.2 16.44 1 36 0 0
#> 78.3 23.88 1 43 0 0
#> 85.3 16.44 1 36 0 0
#> 129 23.41 1 53 1 0
#> 181 16.46 1 45 0 1
#> 97.1 19.14 1 65 0 1
#> 190 20.81 1 42 1 0
#> 110.2 17.56 1 65 0 1
#> 88 18.37 1 47 0 0
#> 140.1 12.68 1 59 1 0
#> 42 12.43 1 49 0 1
#> 187 9.92 1 39 1 0
#> 129.1 23.41 1 53 1 0
#> 93 10.33 1 52 0 1
#> 63 22.77 1 31 1 0
#> 86.1 23.81 1 58 0 1
#> 129.2 23.41 1 53 1 0
#> 42.1 12.43 1 49 0 1
#> 197 21.60 1 69 1 0
#> 15 22.68 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 190.1 20.81 1 42 1 0
#> 8 18.43 1 32 0 0
#> 41.2 18.02 1 40 1 0
#> 189 10.51 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 96.1 14.54 1 33 0 1
#> 63.1 22.77 1 31 1 0
#> 145.2 10.07 1 65 1 0
#> 105.2 19.75 1 60 0 0
#> 192 16.44 1 31 1 0
#> 6.1 15.64 1 39 0 0
#> 86.2 23.81 1 58 0 1
#> 40 18.00 1 28 1 0
#> 175.1 21.91 1 43 0 0
#> 133.1 14.65 1 57 0 0
#> 113 22.86 1 34 0 0
#> 58 19.34 1 39 0 0
#> 4.1 17.64 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 4.2 17.64 1 NA 0 1
#> 30.2 17.43 1 78 0 0
#> 190.2 20.81 1 42 1 0
#> 2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 182 24.00 0 35 0 0
#> 148 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 17 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 163 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 17.1 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 21 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 151 24.00 0 42 0 0
#> 198.1 24.00 0 66 0 1
#> 161 24.00 0 45 0 0
#> 19.1 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 64 24.00 0 43 0 0
#> 27 24.00 0 63 1 0
#> 75 24.00 0 21 1 0
#> 119 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 165 24.00 0 47 0 0
#> 12.1 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 131 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 62 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 193.1 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 3 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 102 24.00 0 49 0 0
#> 148.1 24.00 0 61 1 0
#> 71.1 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#> 71.2 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 65.1 24.00 0 57 1 0
#> 186.1 24.00 0 45 1 0
#> 64.1 24.00 0 43 0 0
#> 38.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 62.1 24.00 0 71 0 0
#> 148.2 24.00 0 61 1 0
#> 35.1 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 11 24.00 0 42 0 1
#> 163.1 24.00 0 66 0 0
#> 144.1 24.00 0 28 0 1
#> 83 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 132.1 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 126 24.00 0 48 0 0
#> 174.1 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 102.1 24.00 0 49 0 0
#> 47.1 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 131.1 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 182.1 24.00 0 35 0 0
#> 116.1 24.00 0 58 0 1
#> 160.1 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 137 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 182.2 24.00 0 35 0 0
#> 135.1 24.00 0 58 1 0
#> 11.1 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.383 NA NA NA
#> 2 age, Cure model 0.00761 NA NA NA
#> 3 grade_ii, Cure model 0.129 NA NA NA
#> 4 grade_iii, Cure model 0.614 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00735 NA NA NA
#> 2 grade_ii, Survival model 0.405 NA NA NA
#> 3 grade_iii, Survival model 0.430 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.383383 0.007607 0.128801 0.614042
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 258.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.38338316 0.00760682 0.12880101 0.61404223
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007349469 0.405182053 0.429613096
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.748971988 0.413219111 0.241441034 0.530172856 0.748971988 0.151569102
#> [7] 0.748971988 0.008517339 0.819312062 0.588120799 0.638157668 0.869520459
#> [13] 0.578190891 0.288400368 0.055700966 0.799086554 0.969884768 0.481189202
#> [19] 0.909711937 0.033574656 0.738875474 0.461395711 0.337130970 0.698514490
#> [25] 0.187950657 0.819312062 0.979954150 0.432425500 0.241441034 0.500815845
#> [31] 0.788916264 0.337130970 0.008517339 0.269284721 0.223266685 0.375216987
#> [37] 0.608050958 0.909711937 0.107722646 0.638157668 0.658121030 0.384873044
#> [43] 0.008517339 0.949732109 0.979954150 0.618087130 0.471254908 0.432425500
#> [49] 0.064927874 0.530172856 0.728760418 0.748971988 0.064927874 0.959817324
#> [55] 0.869520459 0.678268332 0.500815845 0.422831879 0.327280092 0.718640689
#> [61] 0.668172500 0.889567366 0.384873044 0.178686105 0.530172856 0.008517339
#> [67] 0.530172856 0.082662209 0.520337880 0.288400368 0.197186122 0.384873044
#> [73] 0.317383452 0.799086554 0.839391580 0.939656319 0.082662209 0.899642390
#> [79] 0.125659084 0.033574656 0.082662209 0.839391580 0.169448568 0.142644317
#> [85] 0.223266685 0.197186122 0.307576152 0.337130970 0.481189202 0.698514490
#> [91] 0.125659084 0.909711937 0.241441034 0.530172856 0.618087130 0.033574656
#> [97] 0.365545619 0.151569102 0.678268332 0.116614489 0.269284721 0.859436616
#> [103] 0.588120799 0.432425500 0.197186122 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 155 117 105 85 155.1 175 155.2 78 154 100 39 107 5
#> 13.08 17.46 19.75 16.44 13.08 21.91 13.08 23.88 12.63 16.07 15.59 11.18 16.43
#> 97 168 140 91 106 145 86 60 45 41 96 90 154.1
#> 19.14 23.72 12.68 5.33 16.67 10.07 23.81 13.15 17.42 18.02 14.54 20.94 12.63
#> 127 30 105.1 171 123 41.1 78.1 55 150 134 26 145.1 69
#> 3.53 17.43 19.75 16.57 13.00 18.02 23.88 19.34 20.33 17.81 15.77 10.07 23.23
#> 39.1 18 110 78.2 16 127.1 6 23 30.1 164 85.1 13 155.3
#> 15.59 15.21 17.56 23.88 8.71 3.53 15.64 16.92 17.43 23.60 16.44 14.34 13.08
#> 164.1 25 107.1 133 171.1 111 108 57 157 52 110.1 139 85.2
#> 23.60 6.32 11.18 14.65 16.57 17.45 18.29 14.46 15.10 10.42 17.56 21.49 16.44
#> 78.3 85.3 129 181 97.1 190 110.2 88 140.1 42 187 129.1 93
#> 23.88 16.44 23.41 16.46 19.14 20.81 17.56 18.37 12.68 12.43 9.92 23.41 10.33
#> 63 86.1 129.2 42.1 197 15 150.1 190.1 8 41.2 106.1 96.1 63.1
#> 22.77 23.81 23.41 12.43 21.60 22.68 20.33 20.81 18.43 18.02 16.67 14.54 22.77
#> 145.2 105.2 192 6.1 86.2 40 175.1 133.1 113 58 43 100.1 30.2
#> 10.07 19.75 16.44 15.64 23.81 18.00 21.91 14.65 22.86 19.34 12.10 16.07 17.43
#> 190.2 2 182 148 12 17 116 163 71 104 19 17.1 34
#> 20.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 135 65 198 156 151 198.1 161 19.1 132 64 27 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 144 165 12.1 174 9 186 193 131 35 98 196 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 193.1 38 67 3 28 102 148.1 71.1 176 119.1 71.2 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 186.1 64.1 38.1 72 62.1 148.2 35.1 147 11 163.1 144.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 132.1 160 75.1 126 174.1 109 146 122 102.1 47.1 131.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 116.1 160.1 94 137 9.1 182.2 135.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[78]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004357439 0.546660722 0.308533266
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.383907506 0.004394858 0.283641827
#> grade_iii, Cure model
#> 0.840948410
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 97 19.14 1 65 0 1
#> 77 7.27 1 67 0 1
#> 195 11.76 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 69 23.23 1 25 0 1
#> 107 11.18 1 54 1 0
#> 66 22.13 1 53 0 0
#> 187 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 195.1 11.76 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 136 21.83 1 43 0 1
#> 188 16.16 1 46 0 1
#> 41 18.02 1 40 1 0
#> 4 17.64 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 90 20.94 1 50 0 1
#> 111 17.45 1 47 0 1
#> 14 12.89 1 21 0 0
#> 157 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 45 17.42 1 54 0 1
#> 42 12.43 1 49 0 1
#> 125 15.65 1 67 1 0
#> 78 23.88 1 43 0 0
#> 15 22.68 1 48 0 0
#> 14.1 12.89 1 21 0 0
#> 125.1 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 111.1 17.45 1 47 0 1
#> 136.1 21.83 1 43 0 1
#> 195.2 11.76 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 166 19.98 1 48 0 0
#> 158 20.14 1 74 1 0
#> 106 16.67 1 49 1 0
#> 187.1 9.92 1 39 1 0
#> 18 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 63.1 22.77 1 31 1 0
#> 79 16.23 1 54 1 0
#> 4.1 17.64 1 NA 0 1
#> 69.1 23.23 1 25 0 1
#> 153 21.33 1 55 1 0
#> 37 12.52 1 57 1 0
#> 155 13.08 1 26 0 0
#> 61 10.12 1 36 0 1
#> 134 17.81 1 47 1 0
#> 177 12.53 1 75 0 0
#> 199 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 8 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 50 10.02 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 16 8.71 1 71 0 1
#> 140 12.68 1 59 1 0
#> 59 10.16 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 92 22.92 1 47 0 1
#> 158.1 20.14 1 74 1 0
#> 179.1 18.63 1 42 0 0
#> 170 19.54 1 43 0 1
#> 175 21.91 1 43 0 0
#> 192 16.44 1 31 1 0
#> 157.1 15.10 1 47 0 0
#> 136.2 21.83 1 43 0 1
#> 129 23.41 1 53 1 0
#> 70 7.38 1 30 1 0
#> 100 16.07 1 60 0 0
#> 123 13.00 1 44 1 0
#> 4.2 17.64 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 110 17.56 1 65 0 1
#> 60.2 13.15 1 38 1 0
#> 10 10.53 1 34 0 0
#> 194 22.40 1 38 0 1
#> 56 12.21 1 60 0 0
#> 81 14.06 1 34 0 0
#> 150 20.33 1 48 0 0
#> 26.1 15.77 1 49 0 1
#> 32.1 20.90 1 37 1 0
#> 166.1 19.98 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 168 23.72 1 70 0 0
#> 194.1 22.40 1 38 0 1
#> 197 21.60 1 69 1 0
#> 127 3.53 1 62 0 1
#> 8.1 18.43 1 32 0 0
#> 130 16.47 1 53 0 1
#> 8.2 18.43 1 32 0 0
#> 140.1 12.68 1 59 1 0
#> 56.1 12.21 1 60 0 0
#> 99 21.19 1 38 0 1
#> 36.1 21.19 1 48 0 1
#> 97.1 19.14 1 65 0 1
#> 125.2 15.65 1 67 1 0
#> 18.1 15.21 1 49 1 0
#> 18.2 15.21 1 49 1 0
#> 50.1 10.02 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 91 5.33 1 61 0 1
#> 29 15.45 1 68 1 0
#> 51 18.23 1 83 0 1
#> 139 21.49 1 63 1 0
#> 108 18.29 1 39 0 1
#> 52 10.42 1 52 0 1
#> 168.1 23.72 1 70 0 0
#> 37.1 12.52 1 57 1 0
#> 17 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 71 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 118 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 83 24.00 0 6 0 0
#> 94 24.00 0 51 0 1
#> 131 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 9 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 121 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 102 24.00 0 49 0 0
#> 122 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 131.1 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 34 24.00 0 36 0 0
#> 109 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 121.2 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 174.1 24.00 0 49 1 0
#> 103 24.00 0 56 1 0
#> 87.1 24.00 0 27 0 0
#> 137 24.00 0 45 1 0
#> 34.1 24.00 0 36 0 0
#> 147 24.00 0 76 1 0
#> 28 24.00 0 67 1 0
#> 122.1 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 200 24.00 0 64 0 0
#> 152 24.00 0 36 0 1
#> 12.1 24.00 0 63 0 0
#> 3 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 196 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 174.2 24.00 0 49 1 0
#> 87.2 24.00 0 27 0 0
#> 28.1 24.00 0 67 1 0
#> 103.1 24.00 0 56 1 0
#> 19 24.00 0 57 0 1
#> 22.1 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 103.2 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 84.2 24.00 0 39 0 1
#> 172 24.00 0 41 0 0
#> 152.1 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 84.3 24.00 0 39 0 1
#> 94.2 24.00 0 51 0 1
#> 131.2 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 118.1 24.00 0 44 1 0
#> 122.2 24.00 0 66 0 0
#> 122.3 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 182 24.00 0 35 0 0
#> 28.2 24.00 0 67 1 0
#> 2 24.00 0 9 0 0
#> 109.1 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 156.1 24.00 0 50 1 0
#> 84.4 24.00 0 39 0 1
#> 7.1 24.00 0 37 1 0
#> 160.1 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 156.2 24.00 0 50 1 0
#> 182.1 24.00 0 35 0 0
#> 200.1 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.384 NA NA NA
#> 2 age, Cure model 0.00439 NA NA NA
#> 3 grade_ii, Cure model 0.284 NA NA NA
#> 4 grade_iii, Cure model 0.841 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00436 NA NA NA
#> 2 grade_ii, Survival model 0.547 NA NA NA
#> 3 grade_iii, Survival model 0.309 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.383908 0.004395 0.283642 0.840948
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 255.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.383907506 0.004394858 0.283641827 0.840948410
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004357439 0.546660722 0.308533266
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.52329159 0.98282794 0.40625551 0.16811398 0.91763011 0.30758146
#> [7] 0.95959294 0.02789691 0.75584119 0.33494948 0.70528293 0.60170459
#> [13] 0.81010632 0.43727459 0.64300966 0.84264955 0.78997286 0.22185966
#> [19] 0.61015254 0.66676625 0.65886130 0.89321453 0.73483551 0.06509943
#> [25] 0.25152334 0.84264955 0.73483551 0.95367649 0.64300966 0.33494948
#> [31] 0.25152334 0.49577037 0.47724841 0.67464276 0.95959294 0.76986699
#> [37] 0.72021265 0.22185966 0.69775342 0.16811398 0.39506756 0.88086624
#> [43] 0.82961107 0.94176412 0.61849064 0.87456260 0.54095423 0.55850187
#> [49] 0.44769402 0.81010632 0.97123940 0.85556351 0.92369418 0.86824135
#> [55] 0.20409632 0.47724841 0.54095423 0.51413283 0.32132546 0.69012632
#> [61] 0.78997286 0.33494948 0.14652537 0.97705032 0.71275947 0.83615808
#> [67] 0.62670470 0.63489943 0.81010632 0.92973078 0.28039952 0.90544691
#> [73] 0.80338236 0.46735911 0.72021265 0.44769402 0.49577037 0.89321453
#> [79] 0.09898816 0.28039952 0.37144490 0.99430173 0.55850187 0.68241594
#> [85] 0.55850187 0.85556351 0.90544691 0.40625551 0.40625551 0.52329159
#> [91] 0.73483551 0.76986699 0.76986699 0.94774450 0.98857775 0.76289674
#> [97] 0.59312945 0.38348769 0.58443431 0.93576114 0.09898816 0.88086624
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 97 77 36 69 107 66 187 24 6 136 188 41 60
#> 19.14 7.27 21.19 23.23 11.18 22.13 9.92 23.89 15.64 21.83 16.16 18.02 13.15
#> 90 111 14 157 63 40 23 45 42 125 78 15 14.1
#> 20.94 17.45 12.89 15.10 22.77 18.00 16.92 17.42 12.43 15.65 23.88 22.68 12.89
#> 125.1 101 111.1 136.1 15.1 166 158 106 187.1 18 26 63.1 79
#> 15.65 9.97 17.45 21.83 22.68 19.98 20.14 16.67 9.92 15.21 15.77 22.77 16.23
#> 69.1 153 37 155 61 134 177 179 8 32 60.1 16 140
#> 23.23 21.33 12.52 13.08 10.12 17.81 12.53 18.63 18.43 20.90 13.15 8.71 12.68
#> 159 154 92 158.1 179.1 170 175 192 157.1 136.2 129 70 100
#> 10.55 12.63 22.92 20.14 18.63 19.54 21.91 16.44 15.10 21.83 23.41 7.38 16.07
#> 123 184 110 60.2 10 194 56 81 150 26.1 32.1 166.1 42.1
#> 13.00 17.77 17.56 13.15 10.53 22.40 12.21 14.06 20.33 15.77 20.90 19.98 12.43
#> 168 194.1 197 127 8.1 130 8.2 140.1 56.1 99 36.1 97.1 125.2
#> 23.72 22.40 21.60 3.53 18.43 16.47 18.43 12.68 12.21 21.19 21.19 19.14 15.65
#> 18.1 18.2 145 91 29 51 139 108 52 168.1 37.1 17 156
#> 15.21 15.21 10.07 5.33 15.45 18.23 21.49 18.29 10.42 23.72 12.52 24.00 24.00
#> 71 84 84.1 118 144 83 94 131 7 64 9 12 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 102 122 22 131.1 87 34 109 121.1 121.2 21 174.1 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 137 34.1 147 28 122.1 1 200 152 12.1 3 147.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 160 3.1 38 174.2 87.2 28.1 103.1 19 22.1 193 103.2 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 35 84.2 172 152.1 132 84.3 94.2 131.2 172.1 118.1 122.2 122.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 98 182 28.2 2 109.1 143.1 119 156.1 84.4 7.1 160.1 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 53 191 120 156.2 182.1 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[79]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002234821 1.600995889 0.603855643
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.00375151 0.01220947 0.59295474
#> grade_iii, Cure model
#> 1.60496416
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 117 17.46 1 26 0 1
#> 155 13.08 1 26 0 0
#> 154 12.63 1 20 1 0
#> 77 7.27 1 67 0 1
#> 128 20.35 1 35 0 1
#> 106 16.67 1 49 1 0
#> 45 17.42 1 54 0 1
#> 90 20.94 1 50 0 1
#> 30 17.43 1 78 0 0
#> 37 12.52 1 57 1 0
#> 15 22.68 1 48 0 0
#> 99 21.19 1 38 0 1
#> 134 17.81 1 47 1 0
#> 70 7.38 1 30 1 0
#> 57 14.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 168 23.72 1 70 0 0
#> 91 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 195 11.76 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 23 16.92 1 61 0 0
#> 107 11.18 1 54 1 0
#> 134.1 17.81 1 47 1 0
#> 110 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 167 15.55 1 56 1 0
#> 168.1 23.72 1 70 0 0
#> 99.1 21.19 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 195.1 11.76 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 23.1 16.92 1 61 0 0
#> 177 12.53 1 75 0 0
#> 171 16.57 1 41 0 1
#> 145 10.07 1 65 1 0
#> 69 23.23 1 25 0 1
#> 15.1 22.68 1 48 0 0
#> 90.1 20.94 1 50 0 1
#> 117.1 17.46 1 26 0 1
#> 140 12.68 1 59 1 0
#> 70.1 7.38 1 30 1 0
#> 187.1 9.92 1 39 1 0
#> 134.2 17.81 1 47 1 0
#> 129 23.41 1 53 1 0
#> 49 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 36 21.19 1 48 0 1
#> 68 20.62 1 44 0 0
#> 14 12.89 1 21 0 0
#> 70.2 7.38 1 30 1 0
#> 123 13.00 1 44 1 0
#> 168.2 23.72 1 70 0 0
#> 36.1 21.19 1 48 0 1
#> 107.1 11.18 1 54 1 0
#> 192.1 16.44 1 31 1 0
#> 69.1 23.23 1 25 0 1
#> 24 23.89 1 38 0 0
#> 188 16.16 1 46 0 1
#> 8 18.43 1 32 0 0
#> 45.1 17.42 1 54 0 1
#> 145.1 10.07 1 65 1 0
#> 169 22.41 1 46 0 0
#> 77.1 7.27 1 67 0 1
#> 56.1 12.21 1 60 0 0
#> 145.2 10.07 1 65 1 0
#> 86 23.81 1 58 0 1
#> 15.2 22.68 1 48 0 0
#> 61 10.12 1 36 0 1
#> 89 11.44 1 NA 0 0
#> 106.1 16.67 1 49 1 0
#> 171.1 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 60.1 13.15 1 38 1 0
#> 25 6.32 1 34 1 0
#> 66 22.13 1 53 0 0
#> 145.3 10.07 1 65 1 0
#> 107.2 11.18 1 54 1 0
#> 37.1 12.52 1 57 1 0
#> 68.1 20.62 1 44 0 0
#> 195.2 11.76 1 NA 1 0
#> 117.2 17.46 1 26 0 1
#> 168.3 23.72 1 70 0 0
#> 170.1 19.54 1 43 0 1
#> 23.2 16.92 1 61 0 0
#> 150 20.33 1 48 0 0
#> 97 19.14 1 65 0 1
#> 25.1 6.32 1 34 1 0
#> 130 16.47 1 53 0 1
#> 18 15.21 1 49 1 0
#> 18.1 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 99.2 21.19 1 38 0 1
#> 24.1 23.89 1 38 0 0
#> 43 12.10 1 61 0 1
#> 36.2 21.19 1 48 0 1
#> 93 10.33 1 52 0 1
#> 76 19.22 1 54 0 1
#> 39 15.59 1 37 0 1
#> 111 17.45 1 47 0 1
#> 43.1 12.10 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 45.2 17.42 1 54 0 1
#> 93.1 10.33 1 52 0 1
#> 189.1 10.51 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 117.3 17.46 1 26 0 1
#> 136 21.83 1 43 0 1
#> 97.1 19.14 1 65 0 1
#> 189.2 10.51 1 NA 1 0
#> 64 24.00 0 43 0 0
#> 35 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 131 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 74 24.00 0 43 0 1
#> 34 24.00 0 36 0 0
#> 7 24.00 0 37 1 0
#> 151 24.00 0 42 0 0
#> 148 24.00 0 61 1 0
#> 122 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 67.1 24.00 0 25 0 0
#> 109 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 28 24.00 0 67 1 0
#> 160 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 200 24.00 0 64 0 0
#> 172.1 24.00 0 41 0 0
#> 115 24.00 0 NA 1 0
#> 102 24.00 0 49 0 0
#> 138.1 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 94 24.00 0 51 0 1
#> 172.2 24.00 0 41 0 0
#> 28.1 24.00 0 67 1 0
#> 174 24.00 0 49 1 0
#> 196 24.00 0 19 0 0
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 185.1 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 132.1 24.00 0 55 0 0
#> 95.1 24.00 0 68 0 1
#> 67.2 24.00 0 25 0 0
#> 148.1 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 34.1 24.00 0 36 0 0
#> 47 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 44.1 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 67.3 24.00 0 25 0 0
#> 7.1 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 132.2 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 131.1 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 67.4 24.00 0 25 0 0
#> 7.2 24.00 0 37 1 0
#> 148.2 24.00 0 61 1 0
#> 185.2 24.00 0 44 1 0
#> 160.1 24.00 0 31 1 0
#> 115.1 24.00 0 NA 1 0
#> 83 24.00 0 6 0 0
#> 73.1 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 75.1 24.00 0 21 1 0
#> 116.1 24.00 0 58 0 1
#> 116.2 24.00 0 58 0 1
#> 185.3 24.00 0 44 1 0
#> 151.1 24.00 0 42 0 0
#> 74.1 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 20.1 24.00 0 46 1 0
#> 132.3 24.00 0 55 0 0
#> 72 24.00 0 40 0 1
#> 176 24.00 0 43 0 1
#> 34.2 24.00 0 36 0 0
#> 178.1 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 67.5 24.00 0 25 0 0
#> 19.1 24.00 0 57 0 1
#> 143 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.00 NA NA NA
#> 2 age, Cure model 0.0122 NA NA NA
#> 3 grade_ii, Cure model 0.593 NA NA NA
#> 4 grade_iii, Cure model 1.60 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00223 NA NA NA
#> 2 grade_ii, Survival model 1.60 NA NA NA
#> 3 grade_iii, Survival model 0.604 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00375 0.01221 0.59295 1.60496
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 240 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00375151 0.01220947 0.59295474 1.60496416
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002234821 1.600995889 0.603855643
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.80489204 0.66679452 0.86563878 0.88497293 0.98359787 0.52725044
#> [7] 0.75845874 0.71366654 0.48064656 0.70584014 0.89418680 0.31588123
#> [13] 0.41054014 0.62505282 0.97352181 0.85052602 0.96647868 0.16903961
#> [19] 0.99676264 0.56167103 0.65004973 0.73611237 0.92449064 0.62505282
#> [25] 0.65848147 0.90295542 0.83446904 0.16903961 0.41054014 0.85575067
#> [31] 0.55022957 0.73611237 0.88958204 0.77220117 0.94828680 0.28332451
#> [37] 0.31588123 0.48064656 0.66679452 0.88026112 0.97352181 0.96647868
#> [43] 0.62505282 0.26446647 0.91171183 0.79242058 0.41054014 0.50400405
#> [49] 0.87542887 0.97352181 0.87059533 0.16903961 0.41054014 0.92449064
#> [55] 0.79242058 0.28332451 0.05334524 0.81093616 0.61471898 0.71366654
#> [61] 0.94828680 0.36265287 0.98359787 0.90295542 0.94828680 0.13366915
#> [67] 0.31588123 0.94434091 0.75845874 0.77220117 0.81693436 0.85575067
#> [73] 0.99027539 0.37888731 0.94828680 0.92449064 0.89418680 0.50400405
#> [79] 0.66679452 0.16903961 0.56167103 0.73611237 0.53875387 0.59419967
#> [85] 0.99027539 0.78570221 0.84004314 0.84004314 0.96283331 0.41054014
#> [91] 0.05334524 0.91600716 0.41054014 0.93643322 0.58343162 0.82871747
#> [97] 0.69799717 0.91600716 0.71366654 0.93643322 0.82292625 0.66679452
#> [103] 0.39503487 0.59419967 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 79 117 155 154 77 128 106 45 90 30 37 15 99
#> 16.23 17.46 13.08 12.63 7.27 20.35 16.67 17.42 20.94 17.43 12.52 22.68 21.19
#> 134 70 57 187 168 91 170 184 23 107 134.1 110 56
#> 17.81 7.38 14.46 9.92 23.72 5.33 19.54 17.77 16.92 11.18 17.81 17.56 12.21
#> 167 168.1 99.1 60 105 23.1 177 171 145 69 15.1 90.1 117.1
#> 15.55 23.72 21.19 13.15 19.75 16.92 12.53 16.57 10.07 23.23 22.68 20.94 17.46
#> 140 70.1 187.1 134.2 129 49 192 36 68 14 70.2 123 168.2
#> 12.68 7.38 9.92 17.81 23.41 12.19 16.44 21.19 20.62 12.89 7.38 13.00 23.72
#> 36.1 107.1 192.1 69.1 24 188 8 45.1 145.1 169 77.1 56.1 145.2
#> 21.19 11.18 16.44 23.23 23.89 16.16 18.43 17.42 10.07 22.41 7.27 12.21 10.07
#> 86 15.2 61 106.1 171.1 100 60.1 25 66 145.3 107.2 37.1 68.1
#> 23.81 22.68 10.12 16.67 16.57 16.07 13.15 6.32 22.13 10.07 11.18 12.52 20.62
#> 117.2 168.3 170.1 23.2 150 97 25.1 130 18 18.1 101 99.2 24.1
#> 17.46 23.72 19.54 16.92 20.33 19.14 6.32 16.47 15.21 15.21 9.97 21.19 23.89
#> 43 36.2 93 76 39 111 43.1 45.2 93.1 125 117.3 136 97.1
#> 12.10 21.19 10.33 19.22 15.59 17.45 12.10 17.42 10.33 15.65 17.46 21.83 19.14
#> 64 35 132 131 185 138 67 74 34 7 151 148 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 67.1 109 28 160 172 200 172.1 102 138.1 118 1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.2 28.1 174 196 163 62 185.1 95 21 22 12 48 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 95.1 67.2 148.1 19 44 34.1 47 182 44.1 116 67.3 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 20 132.2 75 131.1 178 22.1 67.4 7.2 148.2 185.2 160.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 2 75.1 116.1 116.2 185.3 151.1 74.1 71 20.1 132.3 72 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 178.1 135 67.5 19.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[80]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008223425 0.372457362 0.713492800
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.60608479 0.01035568 0.05343098
#> grade_iii, Cure model
#> 1.27550813
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 93 10.33 1 52 0 1
#> 85 16.44 1 36 0 0
#> 113 22.86 1 34 0 0
#> 14 12.89 1 21 0 0
#> 179 18.63 1 42 0 0
#> 134 17.81 1 47 1 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 108 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 63 22.77 1 31 1 0
#> 153.1 21.33 1 55 1 0
#> 159 10.55 1 50 0 1
#> 59.1 10.16 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 51 18.23 1 83 0 1
#> 175 21.91 1 43 0 0
#> 24 23.89 1 38 0 0
#> 140 12.68 1 59 1 0
#> 15 22.68 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 24.1 23.89 1 38 0 0
#> 134.1 17.81 1 47 1 0
#> 97 19.14 1 65 0 1
#> 25 6.32 1 34 1 0
#> 16 8.71 1 71 0 1
#> 114 13.68 1 NA 0 0
#> 16.1 8.71 1 71 0 1
#> 40 18.00 1 28 1 0
#> 52 10.42 1 52 0 1
#> 96.1 14.54 1 33 0 1
#> 14.1 12.89 1 21 0 0
#> 36 21.19 1 48 0 1
#> 139 21.49 1 63 1 0
#> 166 19.98 1 48 0 0
#> 159.1 10.55 1 50 0 1
#> 184 17.77 1 38 0 0
#> 189 10.51 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 117 17.46 1 26 0 1
#> 171 16.57 1 41 0 1
#> 99 21.19 1 38 0 1
#> 63.1 22.77 1 31 1 0
#> 99.1 21.19 1 38 0 1
#> 51.1 18.23 1 83 0 1
#> 70 7.38 1 30 1 0
#> 59.2 10.16 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 134.2 17.81 1 47 1 0
#> 140.2 12.68 1 59 1 0
#> 169 22.41 1 46 0 0
#> 42 12.43 1 49 0 1
#> 192 16.44 1 31 1 0
#> 59.3 10.16 1 NA 1 0
#> 153.2 21.33 1 55 1 0
#> 117.1 17.46 1 26 0 1
#> 60 13.15 1 38 1 0
#> 108.1 18.29 1 39 0 1
#> 76.1 19.22 1 54 0 1
#> 66 22.13 1 53 0 0
#> 16.2 8.71 1 71 0 1
#> 167 15.55 1 56 1 0
#> 189.1 10.51 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 89 11.44 1 NA 0 0
#> 130 16.47 1 53 0 1
#> 139.1 21.49 1 63 1 0
#> 166.1 19.98 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 59.4 10.16 1 NA 1 0
#> 139.2 21.49 1 63 1 0
#> 154 12.63 1 20 1 0
#> 42.2 12.43 1 49 0 1
#> 184.1 17.77 1 38 0 0
#> 68 20.62 1 44 0 0
#> 85.2 16.44 1 36 0 0
#> 88 18.37 1 47 0 0
#> 197 21.60 1 69 1 0
#> 30 17.43 1 78 0 0
#> 139.3 21.49 1 63 1 0
#> 43 12.10 1 61 0 1
#> 85.3 16.44 1 36 0 0
#> 177 12.53 1 75 0 0
#> 130.1 16.47 1 53 0 1
#> 8 18.43 1 32 0 0
#> 25.1 6.32 1 34 1 0
#> 69 23.23 1 25 0 1
#> 30.1 17.43 1 78 0 0
#> 153.3 21.33 1 55 1 0
#> 194 22.40 1 38 0 1
#> 155 13.08 1 26 0 0
#> 41 18.02 1 40 1 0
#> 128 20.35 1 35 0 1
#> 6 15.64 1 39 0 0
#> 158 20.14 1 74 1 0
#> 97.1 19.14 1 65 0 1
#> 170 19.54 1 43 0 1
#> 167.1 15.55 1 56 1 0
#> 41.1 18.02 1 40 1 0
#> 29 15.45 1 68 1 0
#> 108.2 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 170.1 19.54 1 43 0 1
#> 77 7.27 1 67 0 1
#> 6.1 15.64 1 39 0 0
#> 150 20.33 1 48 0 0
#> 78 23.88 1 43 0 0
#> 15.1 22.68 1 48 0 0
#> 114.1 13.68 1 NA 0 0
#> 193 24.00 0 45 0 1
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 83 24.00 0 6 0 0
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 148 24.00 0 61 1 0
#> 182 24.00 0 35 0 0
#> 172 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 143 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 83.1 24.00 0 6 0 0
#> 65 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 146 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 148.2 24.00 0 61 1 0
#> 103.1 24.00 0 56 1 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 75.1 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 115 24.00 0 NA 1 0
#> 71 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 33.1 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 38.1 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 84 24.00 0 39 0 1
#> 94 24.00 0 51 0 1
#> 115.1 24.00 0 NA 1 0
#> 142 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 172.1 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 65.1 24.00 0 57 1 0
#> 84.1 24.00 0 39 0 1
#> 64 24.00 0 43 0 0
#> 71.1 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 28 24.00 0 67 1 0
#> 38.2 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 12 24.00 0 63 0 0
#> 104 24.00 0 50 1 0
#> 83.2 24.00 0 6 0 0
#> 173 24.00 0 19 0 1
#> 75.2 24.00 0 21 1 0
#> 73.1 24.00 0 NA 0 1
#> 115.2 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 53.1 24.00 0 32 0 1
#> 83.3 24.00 0 6 0 0
#> 151 24.00 0 42 0 0
#> 135.1 24.00 0 58 1 0
#> 137.1 24.00 0 45 1 0
#> 44.1 24.00 0 56 0 0
#> 142.1 24.00 0 53 0 0
#> 143.2 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 104.1 24.00 0 50 1 0
#> 182.1 24.00 0 35 0 0
#> 12.1 24.00 0 63 0 0
#> 160 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 64.1 24.00 0 43 0 0
#> 174 24.00 0 49 1 0
#> 33.2 24.00 0 53 0 0
#> 48.1 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 138 24.00 0 44 1 0
#> 48.2 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 148.3 24.00 0 61 1 0
#> 185.2 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.606 NA NA NA
#> 2 age, Cure model 0.0104 NA NA NA
#> 3 grade_ii, Cure model 0.0534 NA NA NA
#> 4 grade_iii, Cure model 1.28 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00822 NA NA NA
#> 2 grade_ii, Survival model 0.372 NA NA NA
#> 3 grade_iii, Survival model 0.713 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.60608 0.01036 0.05343 1.27551
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.5
#> Residual Deviance: 240.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.60608479 0.01035568 0.05343098 1.27550813
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008223425 0.372457362 0.713492800
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86192020 0.96079172 0.80177941 0.20623706 0.88786942 0.64699185
#> [7] 0.72343125 0.45829185 0.61574190 0.66964132 0.87238095 0.85656448
#> [13] 0.23374322 0.45829185 0.94695816 0.79611782 0.69066317 0.37396761
#> [19] 0.06714489 0.89811336 0.27718497 0.89811336 0.06714489 0.72343125
#> [25] 0.63184618 0.99150031 0.96985230 0.96985230 0.71694279 0.95620462
#> [31] 0.86192020 0.88786942 0.50259033 0.40774285 0.58060157 0.94695816
#> [37] 0.74215537 0.80177941 0.75461402 0.77874760 0.50259033 0.23374322
#> [43] 0.50259033 0.69066317 0.98286654 0.93743946 0.72343125 0.89811336
#> [49] 0.31758079 0.92306491 0.80177941 0.45829185 0.75461402 0.87756614
#> [55] 0.66964132 0.61574190 0.35616023 0.96985230 0.84030740 0.53246228
#> [61] 0.78467639 0.40774285 0.58060157 0.92306491 0.40774285 0.91308855
#> [67] 0.92306491 0.74215537 0.54241269 0.80177941 0.66212724 0.39142263
#> [73] 0.76676618 0.40774285 0.94222731 0.80177941 0.91808829 0.78467639
#> [79] 0.65457272 0.99150031 0.17750252 0.76676618 0.45829185 0.33785315
#> [85] 0.88272136 0.70392763 0.55228416 0.82925988 0.57135930 0.63184618
#> [91] 0.59866297 0.84030740 0.70392763 0.85116926 0.66964132 0.96533264
#> [97] 0.59866297 0.98720741 0.82925988 0.56186091 0.13955734 0.27718497
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 96 93 85 113 14 179 134 153 76 108 57 18 63
#> 14.54 10.33 16.44 22.86 12.89 18.63 17.81 21.33 19.22 18.29 14.46 15.21 22.77
#> 153.1 159 181 51 175 24 140 15 140.1 24.1 134.1 97 25
#> 21.33 10.55 16.46 18.23 21.91 23.89 12.68 22.68 12.68 23.89 17.81 19.14 6.32
#> 16 16.1 40 52 96.1 14.1 36 139 166 159.1 184 85.1 117
#> 8.71 8.71 18.00 10.42 14.54 12.89 21.19 21.49 19.98 10.55 17.77 16.44 17.46
#> 171 99 63.1 99.1 51.1 70 49 134.2 140.2 169 42 192 153.2
#> 16.57 21.19 22.77 21.19 18.23 7.38 12.19 17.81 12.68 22.41 12.43 16.44 21.33
#> 117.1 60 108.1 76.1 66 16.2 167 190 130 139.1 166.1 42.1 139.2
#> 17.46 13.15 18.29 19.22 22.13 8.71 15.55 20.81 16.47 21.49 19.98 12.43 21.49
#> 154 42.2 184.1 68 85.2 88 197 30 139.3 43 85.3 177 130.1
#> 12.63 12.43 17.77 20.62 16.44 18.37 21.60 17.43 21.49 12.10 16.44 12.53 16.47
#> 8 25.1 69 30.1 153.3 194 155 41 128 6 158 97.1 170
#> 18.43 6.32 23.23 17.43 21.33 22.40 13.08 18.02 20.35 15.64 20.14 19.14 19.54
#> 167.1 41.1 29 108.2 187 170.1 77 6.1 150 78 15.1 193 102
#> 15.55 18.02 15.45 18.29 9.92 19.54 7.27 15.64 20.33 23.88 22.68 24.00 24.00
#> 185 38 2 83 75 103 148 182 172 147 143 137 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 33 163 131 67 146 118 148.1 148.2 103.1 87 62 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 71 143.1 33.1 74 53 38.1 126 54 84 94 142 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 48 94.1 65.1 84.1 64 71.1 135 28 38.2 12 104 83.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 75.2 19 53.1 83.3 151 135.1 137.1 44.1 142.1 143.2 185.1 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 12.1 160 126.1 64.1 174 33.2 48.1 112 138 48.2 31 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.3 185.2 178
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[81]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01919427 0.51229392 0.21229392
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.237840142 -0.003692277 -0.371851833
#> grade_iii, Cure model
#> 0.778915481
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 166 19.98 1 48 0 0
#> 136 21.83 1 43 0 1
#> 114 13.68 1 NA 0 0
#> 114.1 13.68 1 NA 0 0
#> 123 13.00 1 44 1 0
#> 86 23.81 1 58 0 1
#> 197 21.60 1 69 1 0
#> 90 20.94 1 50 0 1
#> 41 18.02 1 40 1 0
#> 96 14.54 1 33 0 1
#> 108 18.29 1 39 0 1
#> 63 22.77 1 31 1 0
#> 101 9.97 1 10 0 1
#> 57 14.46 1 45 0 1
#> 52 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 111 17.45 1 47 0 1
#> 175 21.91 1 43 0 0
#> 166.1 19.98 1 48 0 0
#> 129 23.41 1 53 1 0
#> 30 17.43 1 78 0 0
#> 25 6.32 1 34 1 0
#> 79 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 85 16.44 1 36 0 0
#> 181 16.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 14 12.89 1 21 0 0
#> 61 10.12 1 36 0 1
#> 181.1 16.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 169 22.41 1 46 0 0
#> 199 19.81 1 NA 0 1
#> 181.2 16.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 175.1 21.91 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 81 14.06 1 34 0 0
#> 8 18.43 1 32 0 0
#> 69 23.23 1 25 0 1
#> 45 17.42 1 54 0 1
#> 159 10.55 1 50 0 1
#> 18 15.21 1 49 1 0
#> 183 9.24 1 67 1 0
#> 32 20.90 1 37 1 0
#> 101.1 9.97 1 10 0 1
#> 23.1 16.92 1 61 0 0
#> 125 15.65 1 67 1 0
#> 81.1 14.06 1 34 0 0
#> 168 23.72 1 70 0 0
#> 56 12.21 1 60 0 0
#> 139.1 21.49 1 63 1 0
#> 26 15.77 1 49 0 1
#> 92 22.92 1 47 0 1
#> 15 22.68 1 48 0 0
#> 88 18.37 1 47 0 0
#> 184 17.77 1 38 0 0
#> 6 15.64 1 39 0 0
#> 32.1 20.90 1 37 1 0
#> 149 8.37 1 33 1 0
#> 49.1 12.19 1 48 1 0
#> 15.1 22.68 1 48 0 0
#> 52.1 10.42 1 52 0 1
#> 134 17.81 1 47 1 0
#> 51 18.23 1 83 0 1
#> 25.1 6.32 1 34 1 0
#> 43 12.10 1 61 0 1
#> 6.1 15.64 1 39 0 0
#> 113 22.86 1 34 0 0
#> 190 20.81 1 42 1 0
#> 18.1 15.21 1 49 1 0
#> 58 19.34 1 39 0 0
#> 66 22.13 1 53 0 0
#> 124 9.73 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 26.1 15.77 1 49 0 1
#> 106 16.67 1 49 1 0
#> 4.1 17.64 1 NA 0 1
#> 69.1 23.23 1 25 0 1
#> 99 21.19 1 38 0 1
#> 133.1 14.65 1 57 0 0
#> 26.2 15.77 1 49 0 1
#> 169.1 22.41 1 46 0 0
#> 6.2 15.64 1 39 0 0
#> 8.1 18.43 1 32 0 0
#> 90.2 20.94 1 50 0 1
#> 168.1 23.72 1 70 0 0
#> 88.1 18.37 1 47 0 0
#> 159.1 10.55 1 50 0 1
#> 149.1 8.37 1 33 1 0
#> 136.1 21.83 1 43 0 1
#> 39 15.59 1 37 0 1
#> 5 16.43 1 51 0 1
#> 114.2 13.68 1 NA 0 0
#> 170 19.54 1 43 0 1
#> 187 9.92 1 39 1 0
#> 79.1 16.23 1 54 1 0
#> 26.3 15.77 1 49 0 1
#> 180 14.82 1 37 0 0
#> 93 10.33 1 52 0 1
#> 96.1 14.54 1 33 0 1
#> 5.1 16.43 1 51 0 1
#> 149.2 8.37 1 33 1 0
#> 190.1 20.81 1 42 1 0
#> 117 17.46 1 26 0 1
#> 6.3 15.64 1 39 0 0
#> 168.2 23.72 1 70 0 0
#> 13 14.34 1 54 0 1
#> 97 19.14 1 65 0 1
#> 7 24.00 0 37 1 0
#> 19 24.00 0 57 0 1
#> 84 24.00 0 39 0 1
#> 118 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 173 24.00 0 19 0 1
#> 163 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 137.1 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 131 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 22.1 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 182 24.00 0 35 0 0
#> 132 24.00 0 55 0 0
#> 137.2 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 62.1 24.00 0 71 0 0
#> 163.1 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 163.2 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 62.2 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 182.1 24.00 0 35 0 0
#> 12 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 142 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 173.1 24.00 0 19 0 1
#> 104 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 142.1 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 84.1 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 138 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 109.2 24.00 0 48 0 0
#> 95.1 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 82 24.00 0 34 0 0
#> 54 24.00 0 53 1 0
#> 147 24.00 0 76 1 0
#> 182.2 24.00 0 35 0 0
#> 121 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 142.2 24.00 0 53 0 0
#> 75.1 24.00 0 21 1 0
#> 172 24.00 0 41 0 0
#> 19.1 24.00 0 57 0 1
#> 87 24.00 0 27 0 0
#> 200 24.00 0 64 0 0
#> 103.1 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 38 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 95.2 24.00 0 68 0 1
#> 120 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 191 24.00 0 60 0 1
#> 173.2 24.00 0 19 0 1
#> 172.1 24.00 0 41 0 0
#> 146.1 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 21 24.00 0 47 0 0
#> 84.2 24.00 0 39 0 1
#> 118.1 24.00 0 44 1 0
#> 132.1 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 160.1 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 116 24.00 0 58 0 1
#> 119 24.00 0 17 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.238 NA NA NA
#> 2 age, Cure model -0.00369 NA NA NA
#> 3 grade_ii, Cure model -0.372 NA NA NA
#> 4 grade_iii, Cure model 0.779 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0192 NA NA NA
#> 2 grade_ii, Survival model 0.512 NA NA NA
#> 3 grade_iii, Survival model 0.212 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.237840 -0.003692 -0.371852 0.778915
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 254.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.237840142 -0.003692277 -0.371851833 0.778915481
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01919427 0.51229392 0.21229392
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.323450e-01 9.596737e-02 3.279753e-02 6.340389e-01 8.145990e-06
#> [6] 4.048507e-02 5.862002e-02 1.722845e-01 5.326135e-01 1.565303e-01
#> [11] 1.044626e-02 8.442290e-01 5.606763e-01 7.763429e-01 5.050502e-01
#> [16] 2.055269e-01 2.585902e-02 9.596737e-02 2.345398e-03 2.142093e-01
#> [21] 9.649777e-01 3.230444e-01 6.801458e-01 2.910664e-01 2.611557e-01
#> [26] 4.476926e-02 6.492466e-01 8.269697e-01 2.611557e-01 5.606763e-01
#> [31] 1.191407e-03 1.713820e-02 2.611557e-01 7.274362e-01 2.585902e-02
#> [36] 6.041883e-01 1.278081e-01 3.793333e-03 2.231737e-01 7.436085e-01
#> [41] 4.653441e-01 8.956762e-01 7.389552e-02 8.442290e-01 2.323450e-01
#> [46] 3.907300e-01 6.041883e-01 9.553814e-05 6.645734e-01 4.476926e-02
#> [51] 3.451015e-01 6.600868e-03 1.250734e-02 1.417369e-01 1.886108e-01
#> [56] 4.028737e-01 7.389552e-02 9.131678e-01 6.801458e-01 1.250734e-02
#> [61] 7.763429e-01 1.803880e-01 1.642660e-01 9.649777e-01 7.114093e-01
#> [66] 4.028737e-01 8.418139e-03 8.474777e-02 4.653441e-01 1.144190e-01
#> [71] 2.264635e-02 5.862002e-02 3.451015e-01 2.513399e-01 3.793333e-03
#> [76] 5.375172e-02 5.050502e-01 3.451015e-01 1.713820e-02 4.028737e-01
#> [81] 1.278081e-01 5.862002e-02 9.553814e-05 1.417369e-01 7.436085e-01
#> [86] 9.131678e-01 3.279753e-02 4.523003e-01 3.015855e-01 1.080371e-01
#> [91] 8.783667e-01 3.230444e-01 3.451015e-01 4.915714e-01 8.098463e-01
#> [96] 5.326135e-01 3.015855e-01 9.131678e-01 8.474777e-02 1.970236e-01
#> [101] 4.028737e-01 9.553814e-05 5.894281e-01 1.209941e-01 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 23 166 136 123 86 197 90 41 96 108 63 101 57
#> 16.92 19.98 21.83 13.00 23.81 21.60 20.94 18.02 14.54 18.29 22.77 9.97 14.46
#> 52 133 111 175 166.1 129 30 25 79 49 85 181 139
#> 10.42 14.65 17.45 21.91 19.98 23.41 17.43 6.32 16.23 12.19 16.44 16.46 21.49
#> 14 61 181.1 57.1 164 169 181.2 107 175.1 81 8 69 45
#> 12.89 10.12 16.46 14.46 23.60 22.41 16.46 11.18 21.91 14.06 18.43 23.23 17.42
#> 159 18 183 32 101.1 23.1 125 81.1 168 56 139.1 26 92
#> 10.55 15.21 9.24 20.90 9.97 16.92 15.65 14.06 23.72 12.21 21.49 15.77 22.92
#> 15 88 184 6 32.1 149 49.1 15.1 52.1 134 51 25.1 43
#> 22.68 18.37 17.77 15.64 20.90 8.37 12.19 22.68 10.42 17.81 18.23 6.32 12.10
#> 6.1 113 190 18.1 58 66 90.1 26.1 106 69.1 99 133.1 26.2
#> 15.64 22.86 20.81 15.21 19.34 22.13 20.94 15.77 16.67 23.23 21.19 14.65 15.77
#> 169.1 6.2 8.1 90.2 168.1 88.1 159.1 149.1 136.1 39 5 170 187
#> 22.41 15.64 18.43 20.94 23.72 18.37 10.55 8.37 21.83 15.59 16.43 19.54 9.92
#> 79.1 26.3 180 93 96.1 5.1 149.2 190.1 117 6.3 168.2 13 97
#> 16.23 15.77 14.82 10.33 14.54 16.43 8.37 20.81 17.46 15.64 23.72 14.34 19.14
#> 7 19 84 118 35 1 173 163 137 62 22 137.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 65 131 103 22.1 72 182 132 137.2 2 62.1 163.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 163.2 95 185 62.2 126 182.1 12 75 142 186 173.1 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 142.1 146 53 84.1 109 109.1 186.1 138 28 109.2 95.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 54 147 182.2 121 27 142.2 75.1 172 19.1 87 200 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 38 143 95.2 120 174 191 173.2 172.1 146.1 98 21 84.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.1 132.1 160 48 34 160.1 48.1 152 116 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[82]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0116019 0.7149549 0.7853847
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.74390045 0.01255045 -0.05856095
#> grade_iii, Cure model
#> 1.27555366
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 166 19.98 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 150 20.33 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 18.1 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 36 21.19 1 48 0 1
#> 113 22.86 1 34 0 0
#> 124.1 9.73 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 195.1 11.76 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 81 14.06 1 34 0 0
#> 192 16.44 1 31 1 0
#> 158 20.14 1 74 1 0
#> 41 18.02 1 40 1 0
#> 100 16.07 1 60 0 0
#> 177 12.53 1 75 0 0
#> 110 17.56 1 65 0 1
#> 10 10.53 1 34 0 0
#> 15 22.68 1 48 0 0
#> 127 3.53 1 62 0 1
#> 140 12.68 1 59 1 0
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 188 16.16 1 46 0 1
#> 13 14.34 1 54 0 1
#> 39 15.59 1 37 0 1
#> 129 23.41 1 53 1 0
#> 55 19.34 1 69 0 1
#> 168 23.72 1 70 0 0
#> 171 16.57 1 41 0 1
#> 150.1 20.33 1 48 0 0
#> 183 9.24 1 67 1 0
#> 92 22.92 1 47 0 1
#> 16 8.71 1 71 0 1
#> 136 21.83 1 43 0 1
#> 93 10.33 1 52 0 1
#> 127.1 3.53 1 62 0 1
#> 66.1 22.13 1 53 0 0
#> 113.1 22.86 1 34 0 0
#> 40 18.00 1 28 1 0
#> 26 15.77 1 49 0 1
#> 89 11.44 1 NA 0 0
#> 15.1 22.68 1 48 0 0
#> 90 20.94 1 50 0 1
#> 18.2 15.21 1 49 1 0
#> 96 14.54 1 33 0 1
#> 110.1 17.56 1 65 0 1
#> 140.1 12.68 1 59 1 0
#> 159 10.55 1 50 0 1
#> 16.1 8.71 1 71 0 1
#> 5 16.43 1 51 0 1
#> 139 21.49 1 63 1 0
#> 40.1 18.00 1 28 1 0
#> 149 8.37 1 33 1 0
#> 63 22.77 1 31 1 0
#> 16.2 8.71 1 71 0 1
#> 52 10.42 1 52 0 1
#> 50.1 10.02 1 NA 1 0
#> 93.1 10.33 1 52 0 1
#> 157 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 145 10.07 1 65 1 0
#> 187 9.92 1 39 1 0
#> 10.1 10.53 1 34 0 0
#> 14 12.89 1 21 0 0
#> 91 5.33 1 61 0 1
#> 145.1 10.07 1 65 1 0
#> 140.2 12.68 1 59 1 0
#> 111 17.45 1 47 0 1
#> 5.1 16.43 1 51 0 1
#> 179.1 18.63 1 42 0 0
#> 41.1 18.02 1 40 1 0
#> 13.1 14.34 1 54 0 1
#> 192.1 16.44 1 31 1 0
#> 127.2 3.53 1 62 0 1
#> 108 18.29 1 39 0 1
#> 100.1 16.07 1 60 0 0
#> 179.2 18.63 1 42 0 0
#> 107 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 69 23.23 1 25 0 1
#> 78.1 23.88 1 43 0 0
#> 159.1 10.55 1 50 0 1
#> 18.3 15.21 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 140.3 12.68 1 59 1 0
#> 171.1 16.57 1 41 0 1
#> 13.2 14.34 1 54 0 1
#> 158.1 20.14 1 74 1 0
#> 123 13.00 1 44 1 0
#> 40.2 18.00 1 28 1 0
#> 107.1 11.18 1 54 1 0
#> 187.1 9.92 1 39 1 0
#> 106 16.67 1 49 1 0
#> 86 23.81 1 58 0 1
#> 130 16.47 1 53 0 1
#> 127.3 3.53 1 62 0 1
#> 139.1 21.49 1 63 1 0
#> 91.1 5.33 1 61 0 1
#> 189.1 10.51 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 63.1 22.77 1 31 1 0
#> 37 12.52 1 57 1 0
#> 90.1 20.94 1 50 0 1
#> 66.2 22.13 1 53 0 0
#> 89.1 11.44 1 NA 0 0
#> 188.1 16.16 1 46 0 1
#> 61 10.12 1 36 0 1
#> 74 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 143 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 21 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 135 24.00 0 58 1 0
#> 48 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 112 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 118 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 182 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 138 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 71 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 118.1 24.00 0 44 1 0
#> 109.1 24.00 0 48 0 0
#> 112.1 24.00 0 61 0 0
#> 174 24.00 0 49 1 0
#> 74.1 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 103 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#> 27.1 24.00 0 63 1 0
#> 20.2 24.00 0 46 1 0
#> 67 24.00 0 25 0 0
#> 46 24.00 0 71 0 0
#> 104 24.00 0 50 1 0
#> 109.2 24.00 0 48 0 0
#> 135.1 24.00 0 58 1 0
#> 98 24.00 0 34 1 0
#> 144.1 24.00 0 28 0 1
#> 143.1 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 64 24.00 0 43 0 0
#> 109.3 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 1.1 24.00 0 23 1 0
#> 172 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 103.1 24.00 0 56 1 0
#> 200.1 24.00 0 64 0 0
#> 148 24.00 0 61 1 0
#> 73 24.00 0 NA 0 1
#> 75 24.00 0 21 1 0
#> 67.1 24.00 0 25 0 0
#> 46.1 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 20.3 24.00 0 46 1 0
#> 186.1 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 75.1 24.00 0 21 1 0
#> 115 24.00 0 NA 1 0
#> 54 24.00 0 53 1 0
#> 65 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 178.1 24.00 0 52 1 0
#> 160.2 24.00 0 31 1 0
#> 186.2 24.00 0 45 1 0
#> 112.2 24.00 0 61 0 0
#> 121 24.00 0 57 1 0
#> 21.1 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 74.2 24.00 0 43 0 1
#> 103.2 24.00 0 56 1 0
#> 80.1 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 102 24.00 0 49 0 0
#> 17 24.00 0 38 0 1
#> 54.1 24.00 0 53 1 0
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.744 NA NA NA
#> 2 age, Cure model 0.0126 NA NA NA
#> 3 grade_ii, Cure model -0.0586 NA NA NA
#> 4 grade_iii, Cure model 1.28 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0116 NA NA NA
#> 2 grade_ii, Survival model 0.715 NA NA NA
#> 3 grade_iii, Survival model 0.785 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74390 0.01255 -0.05856 1.27555
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 243.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74390045 0.01255045 -0.05856095 1.27555366
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0116019 0.7149549 0.7853847
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6533991 0.8321474 0.9557444 0.6186897 0.8321474 0.7973570 0.5799379
#> [8] 0.3962996 0.4916656 0.8762543 0.7757958 0.6369459 0.6995847 0.8125715
#> [15] 0.9045353 0.7337681 0.9272680 0.4624572 0.9881532 0.8888420 0.8546581
#> [22] 0.1424120 0.8025579 0.8635961 0.8273385 0.3300414 0.6616008 0.2981643
#> [29] 0.7585529 0.6186897 0.9658898 0.3772875 0.9692178 0.5453444 0.9382558
#> [36] 0.9881532 0.4916656 0.3962996 0.7137338 0.8224625 0.4624572 0.5904281
#> [43] 0.8321474 0.8591529 0.7337681 0.8888420 0.9198906 0.9692178 0.7867952
#> [50] 0.5580372 0.7137338 0.9787752 0.4318073 0.9692178 0.9346171 0.9382558
#> [57] 0.8501410 0.6694257 0.9488784 0.9591656 0.9272680 0.8846659 0.9819507
#> [64] 0.9488784 0.8888420 0.7463437 0.7867952 0.6694257 0.6995847 0.8635961
#> [71] 0.7757958 0.9881532 0.6921330 0.8125715 0.6694257 0.9123364 0.5318302
#> [78] 0.3551746 0.1424120 0.9198906 0.8321474 0.8888420 0.7585529 0.8635961
#> [85] 0.6369459 0.8804842 0.7137338 0.9123364 0.9591656 0.7525129 0.2613691
#> [92] 0.7701207 0.9881532 0.5580372 0.9819507 0.6092849 0.4318073 0.9084607
#> [99] 0.5904281 0.4916656 0.8025579 0.9453536 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 166 18 101 150 18.1 79 36 113 66 81 192 158 41
#> 19.98 15.21 9.97 20.33 15.21 16.23 21.19 22.86 22.13 14.06 16.44 20.14 18.02
#> 100 177 110 10 15 127 140 133 78 188 13 39 129
#> 16.07 12.53 17.56 10.53 22.68 3.53 12.68 14.65 23.88 16.16 14.34 15.59 23.41
#> 55 168 171 150.1 183 92 16 136 93 127.1 66.1 113.1 40
#> 19.34 23.72 16.57 20.33 9.24 22.92 8.71 21.83 10.33 3.53 22.13 22.86 18.00
#> 26 15.1 90 18.2 96 110.1 140.1 159 16.1 5 139 40.1 149
#> 15.77 22.68 20.94 15.21 14.54 17.56 12.68 10.55 8.71 16.43 21.49 18.00 8.37
#> 63 16.2 52 93.1 157 179 145 187 10.1 14 91 145.1 140.2
#> 22.77 8.71 10.42 10.33 15.10 18.63 10.07 9.92 10.53 12.89 5.33 10.07 12.68
#> 111 5.1 179.1 41.1 13.1 192.1 127.2 108 100.1 179.2 107 175 69
#> 17.45 16.43 18.63 18.02 14.34 16.44 3.53 18.29 16.07 18.63 11.18 21.91 23.23
#> 78.1 159.1 18.3 140.3 171.1 13.2 158.1 123 40.2 107.1 187.1 106 86
#> 23.88 10.55 15.21 12.68 16.57 14.34 20.14 13.00 18.00 11.18 9.92 16.67 23.81
#> 130 127.3 139.1 91.1 68 63.1 37 90.1 66.2 188.1 61 74 27
#> 16.47 3.53 21.49 5.33 20.62 22.77 12.52 20.94 22.13 16.16 10.12 24.00 24.00
#> 143 200 21 151 135 48 176 3 109 165 144 112 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 118 28 182 47 138 20.1 71 160 160.1 80 118.1 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 174 74.1 198 103 95 27.1 20.2 67 46 104 109.2 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 144.1 143.1 137 64 109.3 38 178 186 33 1.1 172 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 103.1 200.1 148 75 67.1 46.1 173 20.3 186.1 156 7 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 65 132 178.1 160.2 186.2 112.2 121 21.1 62 74.2 103.2 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 102 17 54.1 87 162
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[83]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0185417 0.3219719 0.3142370
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.03075475 0.00467774 -0.38572447
#> grade_iii, Cure model
#> 0.34839956
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 56 12.21 1 60 0 0
#> 197 21.60 1 69 1 0
#> 150 20.33 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 129 23.41 1 53 1 0
#> 157 15.10 1 47 0 0
#> 70 7.38 1 30 1 0
#> 175 21.91 1 43 0 0
#> 106 16.67 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 79 16.23 1 54 1 0
#> 197.1 21.60 1 69 1 0
#> 139 21.49 1 63 1 0
#> 127 3.53 1 62 0 1
#> 170 19.54 1 43 0 1
#> 92 22.92 1 47 0 1
#> 96.1 14.54 1 33 0 1
#> 187 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 158 20.14 1 74 1 0
#> 63 22.77 1 31 1 0
#> 51.1 18.23 1 83 0 1
#> 45 17.42 1 54 0 1
#> 188 16.16 1 46 0 1
#> 26 15.77 1 49 0 1
#> 168 23.72 1 70 0 0
#> 184 17.77 1 38 0 0
#> 130 16.47 1 53 0 1
#> 77 7.27 1 67 0 1
#> 85.1 16.44 1 36 0 0
#> 111 17.45 1 47 0 1
#> 171 16.57 1 41 0 1
#> 155 13.08 1 26 0 0
#> 171.1 16.57 1 41 0 1
#> 90 20.94 1 50 0 1
#> 155.1 13.08 1 26 0 0
#> 110 17.56 1 65 0 1
#> 4 17.64 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 70.1 7.38 1 30 1 0
#> 180 14.82 1 37 0 0
#> 88 18.37 1 47 0 0
#> 100 16.07 1 60 0 0
#> 86 23.81 1 58 0 1
#> 91 5.33 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 154 12.63 1 20 1 0
#> 100.1 16.07 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 96.2 14.54 1 33 0 1
#> 129.1 23.41 1 53 1 0
#> 81 14.06 1 34 0 0
#> 89 11.44 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 159 10.55 1 50 0 1
#> 139.1 21.49 1 63 1 0
#> 197.2 21.60 1 69 1 0
#> 101 9.97 1 10 0 1
#> 154.1 12.63 1 20 1 0
#> 99 21.19 1 38 0 1
#> 55 19.34 1 69 0 1
#> 30 17.43 1 78 0 0
#> 157.1 15.10 1 47 0 0
#> 190 20.81 1 42 1 0
#> 170.2 19.54 1 43 0 1
#> 86.1 23.81 1 58 0 1
#> 183 9.24 1 67 1 0
#> 145 10.07 1 65 1 0
#> 114.1 13.68 1 NA 0 0
#> 171.2 16.57 1 41 0 1
#> 130.1 16.47 1 53 0 1
#> 136 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 175.1 21.91 1 43 0 0
#> 24 23.89 1 38 0 0
#> 66 22.13 1 53 0 0
#> 59 10.16 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 155.2 13.08 1 26 0 0
#> 101.1 9.97 1 10 0 1
#> 5 16.43 1 51 0 1
#> 153 21.33 1 55 1 0
#> 158.1 20.14 1 74 1 0
#> 93 10.33 1 52 0 1
#> 91.1 5.33 1 61 0 1
#> 101.2 9.97 1 10 0 1
#> 15 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 170.3 19.54 1 43 0 1
#> 197.3 21.60 1 69 1 0
#> 139.2 21.49 1 63 1 0
#> 113 22.86 1 34 0 0
#> 181 16.46 1 45 0 1
#> 106.1 16.67 1 49 1 0
#> 25 6.32 1 34 1 0
#> 130.2 16.47 1 53 0 1
#> 154.2 12.63 1 20 1 0
#> 86.2 23.81 1 58 0 1
#> 16 8.71 1 71 0 1
#> 111.1 17.45 1 47 0 1
#> 69 23.23 1 25 0 1
#> 129.2 23.41 1 53 1 0
#> 51.2 18.23 1 83 0 1
#> 37 12.52 1 57 1 0
#> 181.1 16.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 166 19.98 1 48 0 0
#> 115 24.00 0 NA 1 0
#> 87 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 28 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 118 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 103 24.00 0 56 1 0
#> 165 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 62 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 104 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 72.1 24.00 0 40 0 1
#> 28.1 24.00 0 67 1 0
#> 95 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 141 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 118.1 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 75.1 24.00 0 21 1 0
#> 148 24.00 0 61 1 0
#> 137 24.00 0 45 1 0
#> 104.1 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 119.1 24.00 0 17 0 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 118.2 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 95.2 24.00 0 68 0 1
#> 72.2 24.00 0 40 0 1
#> 73 24.00 0 NA 0 1
#> 9 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 94.1 24.00 0 51 0 1
#> 95.3 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 186 24.00 0 45 1 0
#> 19 24.00 0 57 0 1
#> 17 24.00 0 38 0 1
#> 33.1 24.00 0 53 0 0
#> 193.1 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 46 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 135 24.00 0 58 1 0
#> 80 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 3 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 104.2 24.00 0 50 1 0
#> 19.1 24.00 0 57 0 1
#> 173 24.00 0 19 0 1
#> 174 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 44 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 11.1 24.00 0 42 0 1
#> 142 24.00 0 53 0 0
#> 193.2 24.00 0 45 0 1
#> 21 24.00 0 47 0 0
#> 144.1 24.00 0 28 0 1
#> 34.1 24.00 0 36 0 0
#> 116.1 24.00 0 58 0 1
#> 34.2 24.00 0 36 0 0
#> 38 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 62.1 24.00 0 71 0 0
#> 121.1 24.00 0 57 1 0
#> 160.1 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 2 24.00 0 9 0 0
#> 135.2 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0308 NA NA NA
#> 2 age, Cure model 0.00468 NA NA NA
#> 3 grade_ii, Cure model -0.386 NA NA NA
#> 4 grade_iii, Cure model 0.348 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0185 NA NA NA
#> 2 grade_ii, Survival model 0.322 NA NA NA
#> 3 grade_iii, Survival model 0.314 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.030755 0.004678 -0.385724 0.348400
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 257 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.03075475 0.00467774 -0.38572447 0.34839956
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0185417 0.3219719 0.3142370
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.561188e-01 7.001971e-01 3.768724e-02 8.938163e-02 5.084356e-01
#> [6] 5.099975e-03 4.667097e-01 8.791687e-01 2.753251e-02 2.453254e-01
#> [11] 8.623104e-01 3.889603e-01 3.768724e-02 5.334684e-02 9.822000e-01
#> [16] 1.144565e-01 1.196308e-02 5.084356e-01 8.125958e-01 3.529605e-01
#> [21] 9.531516e-02 1.652403e-02 1.561188e-01 2.255254e-01 4.014048e-01
#> [26] 4.398847e-01 2.481629e-03 1.803191e-01 2.969973e-01 9.128294e-01
#> [31] 3.529605e-01 1.978853e-01 2.657230e-01 5.652980e-01 2.657230e-01
#> [36] 7.810096e-02 5.652980e-01 1.889818e-01 6.093441e-01 8.791687e-01
#> [41] 4.942626e-01 1.484809e-01 4.140121e-01 6.909094e-04 9.472776e-01
#> [46] 6.690864e-01 6.245158e-01 4.140121e-01 1.144565e-01 5.084356e-01
#> [51] 5.099975e-03 5.506657e-01 2.397632e-04 7.160827e-01 5.334684e-02
#> [56] 3.768724e-02 7.647777e-01 6.245158e-01 7.270675e-02 1.410649e-01
#> [61] 2.159718e-01 4.667097e-01 8.367155e-02 1.144565e-01 6.909094e-04
#> [66] 8.289667e-01 7.483502e-01 2.657230e-01 2.969973e-01 3.409244e-02
#> [71] 2.161560e-02 2.753251e-02 3.171042e-05 2.446220e-02 4.531950e-01
#> [76] 5.652980e-01 7.647777e-01 3.767090e-01 6.743896e-02 9.531516e-02
#> [81] 7.321315e-01 9.472776e-01 7.647777e-01 1.896919e-02 2.352844e-01
#> [86] 1.144565e-01 3.768724e-02 5.334684e-02 1.415758e-02 3.299658e-01
#> [91] 2.453254e-01 9.300112e-01 2.969973e-01 6.245158e-01 6.909094e-04
#> [96] 8.455345e-01 1.978853e-01 9.928582e-03 5.099975e-03 1.561188e-01
#> [101] 6.845497e-01 3.299658e-01 3.635317e-03 1.077920e-01 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 51 56 197 150 96 129 157 70 175 106 149 79 197.1
#> 18.23 12.21 21.60 20.33 14.54 23.41 15.10 7.38 21.91 16.67 8.37 16.23 21.60
#> 139 127 170 92 96.1 187 85 158 63 51.1 45 188 26
#> 21.49 3.53 19.54 22.92 14.54 9.92 16.44 20.14 22.77 18.23 17.42 16.16 15.77
#> 168 184 130 77 85.1 111 171 155 171.1 90 155.1 110 14
#> 23.72 17.77 16.47 7.27 16.44 17.45 16.57 13.08 16.57 20.94 13.08 17.56 12.89
#> 70.1 180 88 100 86 91 177 154 100.1 170.1 96.2 129.1 81
#> 7.38 14.82 18.37 16.07 23.81 5.33 12.53 12.63 16.07 19.54 14.54 23.41 14.06
#> 78 159 139.1 197.2 101 154.1 99 55 30 157.1 190 170.2 86.1
#> 23.88 10.55 21.49 21.60 9.97 12.63 21.19 19.34 17.43 15.10 20.81 19.54 23.81
#> 183 145 171.2 130.1 136 169 175.1 24 66 6 155.2 101.1 5
#> 9.24 10.07 16.57 16.47 21.83 22.41 21.91 23.89 22.13 15.64 13.08 9.97 16.43
#> 153 158.1 93 91.1 101.2 15 23 170.3 197.3 139.2 113 181 106.1
#> 21.33 20.14 10.33 5.33 9.97 22.68 16.92 19.54 21.60 21.49 22.86 16.46 16.67
#> 25 130.2 154.2 86.2 16 111.1 69 129.2 51.2 37 181.1 164 166
#> 6.32 16.47 12.63 23.81 8.71 17.45 23.23 23.41 18.23 12.52 16.46 23.60 19.98
#> 87 84 28 119 193 118 72 103 165 161 62 48 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 33 198 104 160 12 72.1 28.1 95 22 75 141 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.1 122 94 75.1 148 137 104.1 182 119.1 65 65.1 138 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 118.2 11 95.2 72.2 9 161.1 94.1 95.3 147 186 19 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 193.1 191 46 7 135 80 64 121 3 146 104.2 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 174 34 44 116 11.1 142 193.2 21 144.1 34.1 116.1 34.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 7.1 62.1 121.1 160.1 135.1 2 135.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[84]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00556506 0.37430707 0.30977614
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.689976365 0.005626933 0.441464656
#> grade_iii, Cure model
#> 1.386423336
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 24 23.89 1 38 0 0
#> 88 18.37 1 47 0 0
#> 149 8.37 1 33 1 0
#> 187 9.92 1 39 1 0
#> 108 18.29 1 39 0 1
#> 170 19.54 1 43 0 1
#> 128 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 25 6.32 1 34 1 0
#> 92 22.92 1 47 0 1
#> 187.1 9.92 1 39 1 0
#> 26 15.77 1 49 0 1
#> 187.2 9.92 1 39 1 0
#> 129 23.41 1 53 1 0
#> 68 20.62 1 44 0 0
#> 197 21.60 1 69 1 0
#> 55 19.34 1 69 0 1
#> 61 10.12 1 36 0 1
#> 167 15.55 1 56 1 0
#> 177 12.53 1 75 0 0
#> 13 14.34 1 54 0 1
#> 110 17.56 1 65 0 1
#> 157.1 15.10 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 24.1 23.89 1 38 0 0
#> 106 16.67 1 49 1 0
#> 18 15.21 1 49 1 0
#> 96 14.54 1 33 0 1
#> 63.1 22.77 1 31 1 0
#> 166 19.98 1 48 0 0
#> 139 21.49 1 63 1 0
#> 127 3.53 1 62 0 1
#> 180 14.82 1 37 0 0
#> 177.1 12.53 1 75 0 0
#> 110.1 17.56 1 65 0 1
#> 179 18.63 1 42 0 0
#> 60 13.15 1 38 1 0
#> 41 18.02 1 40 1 0
#> 96.1 14.54 1 33 0 1
#> 105 19.75 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 105.1 19.75 1 60 0 0
#> 42 12.43 1 49 0 1
#> 136 21.83 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 26.1 15.77 1 49 0 1
#> 43 12.10 1 61 0 1
#> 184 17.77 1 38 0 0
#> 183 9.24 1 67 1 0
#> 125 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 136.1 21.83 1 43 0 1
#> 41.1 18.02 1 40 1 0
#> 85 16.44 1 36 0 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 197.1 21.60 1 69 1 0
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 159 10.55 1 50 0 1
#> 13.1 14.34 1 54 0 1
#> 192 16.44 1 31 1 0
#> 108.1 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 114 13.68 1 NA 0 0
#> 23 16.92 1 61 0 0
#> 16.1 8.71 1 71 0 1
#> 97.2 19.14 1 65 0 1
#> 188 16.16 1 46 0 1
#> 40.1 18.00 1 28 1 0
#> 24.2 23.89 1 38 0 0
#> 55.1 19.34 1 69 0 1
#> 130.1 16.47 1 53 0 1
#> 184.1 17.77 1 38 0 0
#> 128.1 20.35 1 35 0 1
#> 184.2 17.77 1 38 0 0
#> 6 15.64 1 39 0 0
#> 30.1 17.43 1 78 0 0
#> 32 20.90 1 37 1 0
#> 188.1 16.16 1 46 0 1
#> 111 17.45 1 47 0 1
#> 70 7.38 1 30 1 0
#> 4 17.64 1 NA 0 1
#> 16.2 8.71 1 71 0 1
#> 170.1 19.54 1 43 0 1
#> 13.2 14.34 1 54 0 1
#> 92.1 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 188.2 16.16 1 46 0 1
#> 158 20.14 1 74 1 0
#> 149.1 8.37 1 33 1 0
#> 110.2 17.56 1 65 0 1
#> 42.1 12.43 1 49 0 1
#> 60.1 13.15 1 38 1 0
#> 49 12.19 1 48 1 0
#> 97.3 19.14 1 65 0 1
#> 195.1 11.76 1 NA 1 0
#> 55.2 19.34 1 69 0 1
#> 128.2 20.35 1 35 0 1
#> 8 18.43 1 32 0 0
#> 128.3 20.35 1 35 0 1
#> 154 12.63 1 20 1 0
#> 93.1 10.33 1 52 0 1
#> 14 12.89 1 21 0 0
#> 127.1 3.53 1 62 0 1
#> 105.2 19.75 1 60 0 0
#> 36 21.19 1 48 0 1
#> 167.1 15.55 1 56 1 0
#> 84 24.00 0 39 0 1
#> 1 24.00 0 23 1 0
#> 62 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 121 24.00 0 57 1 0
#> 126 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 48.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 142 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 115 24.00 0 NA 1 0
#> 33 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 7 24.00 0 37 1 0
#> 34 24.00 0 36 0 0
#> 28 24.00 0 67 1 0
#> 172 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 9 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 193.1 24.00 0 45 0 1
#> 20 24.00 0 46 1 0
#> 121.1 24.00 0 57 1 0
#> 191.1 24.00 0 60 0 1
#> 33.1 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 162.1 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 98 24.00 0 34 1 0
#> 196 24.00 0 19 0 0
#> 142.1 24.00 0 53 0 0
#> 20.1 24.00 0 46 1 0
#> 172.1 24.00 0 41 0 0
#> 142.2 24.00 0 53 0 0
#> 142.3 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 163 24.00 0 66 0 0
#> 20.2 24.00 0 46 1 0
#> 200 24.00 0 64 0 0
#> 165.1 24.00 0 47 0 0
#> 200.1 24.00 0 64 0 0
#> 74 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 102.1 24.00 0 49 0 0
#> 144 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 191.2 24.00 0 60 0 1
#> 156 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 132 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 38.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 161 24.00 0 45 0 0
#> 65.1 24.00 0 57 1 0
#> 95.1 24.00 0 68 0 1
#> 1.1 24.00 0 23 1 0
#> 27 24.00 0 63 1 0
#> 9.1 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 102.2 24.00 0 49 0 0
#> 173 24.00 0 19 0 1
#> 87.1 24.00 0 27 0 0
#> 21 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 95.2 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 131.1 24.00 0 66 0 0
#> 94.1 24.00 0 51 0 1
#> 138.1 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 65.2 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 62.1 24.00 0 71 0 0
#> 1.2 24.00 0 23 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.690 NA NA NA
#> 2 age, Cure model 0.00563 NA NA NA
#> 3 grade_ii, Cure model 0.441 NA NA NA
#> 4 grade_iii, Cure model 1.39 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00557 NA NA NA
#> 2 grade_ii, Survival model 0.374 NA NA NA
#> 3 grade_iii, Survival model 0.310 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.689976 0.005627 0.441465 1.386423
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 249.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.689976365 0.005626933 0.441464656 1.386423336
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00556506 0.37430707 0.30977614
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.78507957 0.21696385 0.05904846 0.55142214 0.96122385 0.92127584
#> [7] 0.55979092 0.44591992 0.35343244 0.97799532 0.98355011 0.18114051
#> [13] 0.92127584 0.73836994 0.92127584 0.15864619 0.34152545 0.27821591
#> [19] 0.46532225 0.91538047 0.76536920 0.86109927 0.81741550 0.63066248
#> [25] 0.78507957 0.13265478 0.05904846 0.68235871 0.77852450 0.80458031
#> [31] 0.21696385 0.40574498 0.30435668 0.98908126 0.79807041 0.86109927
#> [37] 0.63066248 0.53458284 0.83622151 0.57606843 0.80458031 0.41620014
#> [43] 0.68961337 0.41620014 0.87337688 0.24896121 0.73836994 0.89157440
#> [49] 0.60759600 0.93858283 0.75191372 0.94434804 0.24896121 0.57606843
#> [55] 0.70379973 0.50150896 0.50150896 0.27821591 0.90357726 0.59197892
#> [61] 0.89759189 0.81741550 0.70379973 0.55979092 0.66039782 0.67503320
#> [67] 0.94434804 0.50150896 0.71785162 0.59197892 0.05904846 0.46532225
#> [73] 0.68961337 0.60759600 0.35343244 0.60759600 0.75864869 0.66039782
#> [79] 0.32950222 0.71785162 0.65294892 0.97240947 0.94434804 0.44591992
#> [85] 0.81741550 0.18114051 0.49244085 0.71785162 0.39520668 0.96122385
#> [91] 0.63066248 0.87337688 0.83622151 0.88551956 0.50150896 0.46532225
#> [97] 0.35343244 0.54301521 0.35343244 0.85489242 0.90357726 0.84865728
#> [103] 0.98908126 0.41620014 0.31712387 0.76536920 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 157 63 24 88 149 187 108 170 128 77 25 92 187.1
#> 15.10 22.77 23.89 18.37 8.37 9.92 18.29 19.54 20.35 7.27 6.32 22.92 9.92
#> 26 187.2 129 68 197 55 61 167 177 13 110 157.1 86
#> 15.77 9.92 23.41 20.62 21.60 19.34 10.12 15.55 12.53 14.34 17.56 15.10 23.81
#> 24.1 106 18 96 63.1 166 139 127 180 177.1 110.1 179 60
#> 23.89 16.67 15.21 14.54 22.77 19.98 21.49 3.53 14.82 12.53 17.56 18.63 13.15
#> 41 96.1 105 130 105.1 42 136 26.1 43 184 183 125 16
#> 18.02 14.54 19.75 16.47 19.75 12.43 21.83 15.77 12.10 17.77 9.24 15.65 8.71
#> 136.1 41.1 85 97 97.1 197.1 93 40 159 13.1 192 108.1 30
#> 21.83 18.02 16.44 19.14 19.14 21.60 10.33 18.00 10.55 14.34 16.44 18.29 17.43
#> 23 16.1 97.2 188 40.1 24.2 55.1 130.1 184.1 128.1 184.2 6 30.1
#> 16.92 8.71 19.14 16.16 18.00 23.89 19.34 16.47 17.77 20.35 17.77 15.64 17.43
#> 32 188.1 111 70 16.2 170.1 13.2 92.1 76 188.2 158 149.1 110.2
#> 20.90 16.16 17.45 7.38 8.71 19.54 14.34 22.92 19.22 16.16 20.14 8.37 17.56
#> 42.1 60.1 49 97.3 55.2 128.2 8 128.3 154 93.1 14 127.1 105.2
#> 12.43 13.15 12.19 19.14 19.34 20.35 18.43 20.35 12.63 10.33 12.89 3.53 19.75
#> 36 167.1 84 1 62 48 151 121 126 102 48.1 71 193
#> 21.19 15.55 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 95 87 33 162 67 7 34 28 172 191 9 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 20 121.1 191.1 33.1 119 162.1 138 143 135 98 196 142.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 172.1 142.2 142.3 2 165 94 163 20.2 200 165.1 200.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 102.1 144 17 191.2 156 11 132 38 47 38.1 65 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 95.1 1.1 27 9.1 178 137 185 102.2 173 87.1 21 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.2 12 131.1 94.1 138.1 120 198 65.2 80 62.1 1.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[85]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002593217 0.686083026 0.370523944
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.533903692 0.004925987 0.398263302
#> grade_iii, Cure model
#> 1.148218935
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 157 15.10 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 76 19.22 1 54 0 1
#> 52 10.42 1 52 0 1
#> 149 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 114 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 171 16.57 1 41 0 1
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 192 16.44 1 31 1 0
#> 24 23.89 1 38 0 0
#> 187 9.92 1 39 1 0
#> 159 10.55 1 50 0 1
#> 194 22.40 1 38 0 1
#> 63 22.77 1 31 1 0
#> 57 14.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 63.1 22.77 1 31 1 0
#> 153 21.33 1 55 1 0
#> 128 20.35 1 35 0 1
#> 4 17.64 1 NA 0 1
#> 97 19.14 1 65 0 1
#> 42 12.43 1 49 0 1
#> 125 15.65 1 67 1 0
#> 159.1 10.55 1 50 0 1
#> 4.1 17.64 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 140 12.68 1 59 1 0
#> 195 11.76 1 NA 1 0
#> 42.1 12.43 1 49 0 1
#> 166 19.98 1 48 0 0
#> 10 10.53 1 34 0 0
#> 180 14.82 1 37 0 0
#> 107 11.18 1 54 1 0
#> 140.1 12.68 1 59 1 0
#> 150 20.33 1 48 0 0
#> 134 17.81 1 47 1 0
#> 61 10.12 1 36 0 1
#> 192.1 16.44 1 31 1 0
#> 129 23.41 1 53 1 0
#> 136.1 21.83 1 43 0 1
#> 4.2 17.64 1 NA 0 1
#> 61.1 10.12 1 36 0 1
#> 192.2 16.44 1 31 1 0
#> 15 22.68 1 48 0 0
#> 76.1 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 23 16.92 1 61 0 0
#> 41 18.02 1 40 1 0
#> 90 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 169 22.41 1 46 0 0
#> 8 18.43 1 32 0 0
#> 117 17.46 1 26 0 1
#> 39.2 15.59 1 37 0 1
#> 167 15.55 1 56 1 0
#> 93 10.33 1 52 0 1
#> 164 23.60 1 76 0 1
#> 4.3 17.64 1 NA 0 1
#> 41.1 18.02 1 40 1 0
#> 6 15.64 1 39 0 0
#> 183 9.24 1 67 1 0
#> 100 16.07 1 60 0 0
#> 125.1 15.65 1 67 1 0
#> 79 16.23 1 54 1 0
#> 177 12.53 1 75 0 0
#> 41.2 18.02 1 40 1 0
#> 133 14.65 1 57 0 0
#> 169.1 22.41 1 46 0 0
#> 108 18.29 1 39 0 1
#> 110 17.56 1 65 0 1
#> 43 12.10 1 61 0 1
#> 188 16.16 1 46 0 1
#> 168 23.72 1 70 0 0
#> 110.1 17.56 1 65 0 1
#> 194.1 22.40 1 38 0 1
#> 10.1 10.53 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 92 22.92 1 47 0 1
#> 70 7.38 1 30 1 0
#> 177.1 12.53 1 75 0 0
#> 192.3 16.44 1 31 1 0
#> 111.1 17.45 1 47 0 1
#> 194.2 22.40 1 38 0 1
#> 181 16.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 90.1 20.94 1 50 0 1
#> 154 12.63 1 20 1 0
#> 91 5.33 1 61 0 1
#> 36 21.19 1 48 0 1
#> 105.1 19.75 1 60 0 0
#> 50.1 10.02 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 96 14.54 1 33 0 1
#> 105.2 19.75 1 60 0 0
#> 76.2 19.22 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 169.2 22.41 1 46 0 0
#> 40 18.00 1 28 1 0
#> 92.1 22.92 1 47 0 1
#> 150.1 20.33 1 48 0 0
#> 79.1 16.23 1 54 1 0
#> 24.1 23.89 1 38 0 0
#> 86 23.81 1 58 0 1
#> 60 13.15 1 38 1 0
#> 104 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 178 24.00 0 52 1 0
#> 144 24.00 0 28 0 1
#> 1 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 112 24.00 0 61 0 0
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 62 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 53 24.00 0 32 0 1
#> 44 24.00 0 56 0 0
#> 65 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 19 24.00 0 57 0 1
#> 156 24.00 0 50 1 0
#> 186.1 24.00 0 45 1 0
#> 122 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 119.2 24.00 0 17 0 0
#> 196 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 135 24.00 0 58 1 0
#> 122.1 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 62.1 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 2.1 24.00 0 9 0 0
#> 103.1 24.00 0 56 1 0
#> 186.2 24.00 0 45 1 0
#> 119.3 24.00 0 17 0 0
#> 71 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 121 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 62.2 24.00 0 71 0 0
#> 112.1 24.00 0 61 0 0
#> 186.3 24.00 0 45 1 0
#> 191 24.00 0 60 0 1
#> 46 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 46.1 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 193 24.00 0 45 0 1
#> 174 24.00 0 49 1 0
#> 64 24.00 0 43 0 0
#> 7 24.00 0 37 1 0
#> 75 24.00 0 21 1 0
#> 119.4 24.00 0 17 0 0
#> 198.2 24.00 0 66 0 1
#> 137.2 24.00 0 45 1 0
#> 176.1 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 109 24.00 0 48 0 0
#> 12.1 24.00 0 63 0 0
#> 152.1 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 141.2 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 200.1 24.00 0 64 0 0
#> 121.1 24.00 0 57 1 0
#> 200.2 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 75.1 24.00 0 21 1 0
#> 64.1 24.00 0 43 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.534 NA NA NA
#> 2 age, Cure model 0.00493 NA NA NA
#> 3 grade_ii, Cure model 0.398 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00259 NA NA NA
#> 2 grade_ii, Survival model 0.686 NA NA NA
#> 3 grade_iii, Survival model 0.371 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.533904 0.004926 0.398263 1.148219
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 253.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.533903692 0.004925987 0.398263302 1.148218935
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002593217 0.686083026 0.370523944
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.77077294 0.81087585 0.77077294 0.50669440 0.93594186 0.97717917
#> [7] 0.37535265 0.64590440 0.98864383 0.35221910 0.67744117 0.80430796
#> [13] 0.69290271 0.03518217 0.95974360 0.91190120 0.31667517 0.23839127
#> [19] 0.83705769 0.20785178 0.20785178 0.23839127 0.38661846 0.42852766
#> [25] 0.53410749 0.88119965 0.75013154 0.91190120 0.54329191 0.84997082
#> [31] 0.88119965 0.46848381 0.92392874 0.81743686 0.90581520 0.84997082
#> [37] 0.43869864 0.61339112 0.94791794 0.69290271 0.15855416 0.35221910
#> [43] 0.94791794 0.69290271 0.26501063 0.50669440 0.45868358 0.66169945
#> [49] 0.57963860 0.40814701 0.79767206 0.47825696 0.27857991 0.55245850
#> [55] 0.63783163 0.77077294 0.79095973 0.94194242 0.13702890 0.57963860
#> [61] 0.76387610 0.96563119 0.74304985 0.75013154 0.72175290 0.86877952
#> [67] 0.57963860 0.82399256 0.27857991 0.57058801 0.62167662 0.89967623
#> [73] 0.73595678 0.11258617 0.62167662 0.31667517 0.92392874 0.55245850
#> [79] 0.17690227 0.98293066 0.86877952 0.69290271 0.64590440 0.31667517
#> [85] 0.68519932 0.66962836 0.40814701 0.86252785 0.99433321 0.39747607
#> [91] 0.47825696 0.89350792 0.83053997 0.47825696 0.50669440 0.96563119
#> [97] 0.27857991 0.60496410 0.17690227 0.43869864 0.72175290 0.03518217
#> [103] 0.08706864 0.84354370 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 39 157 39.1 76 52 149 197 111 77 136 171 18 192
#> 15.59 15.10 15.59 19.22 10.42 8.37 21.60 17.45 7.27 21.83 16.57 15.21 16.44
#> 24 187 159 194 63 57 113 113.1 63.1 153 128 97 42
#> 23.89 9.92 10.55 22.40 22.77 14.46 22.86 22.86 22.77 21.33 20.35 19.14 12.43
#> 125 159.1 179 140 42.1 166 10 180 107 140.1 150 134 61
#> 15.65 10.55 18.63 12.68 12.43 19.98 10.53 14.82 11.18 12.68 20.33 17.81 10.12
#> 192.1 129 136.1 61.1 192.2 15 76.1 158 23 41 90 29 105
#> 16.44 23.41 21.83 10.12 16.44 22.68 19.22 20.14 16.92 18.02 20.94 15.45 19.75
#> 169 8 117 39.2 167 93 164 41.1 6 183 100 125.1 79
#> 22.41 18.43 17.46 15.59 15.55 10.33 23.60 18.02 15.64 9.24 16.07 15.65 16.23
#> 177 41.2 133 169.1 108 110 43 188 168 110.1 194.1 10.1 8.1
#> 12.53 18.02 14.65 22.41 18.29 17.56 12.10 16.16 23.72 17.56 22.40 10.53 18.43
#> 92 70 177.1 192.3 111.1 194.2 181 106 90.1 154 91 36 105.1
#> 22.92 7.38 12.53 16.44 17.45 22.40 16.46 16.67 20.94 12.63 5.33 21.19 19.75
#> 56 96 105.2 76.2 183.1 169.2 40 92.1 150.1 79.1 24.1 86 60
#> 12.21 14.54 19.75 19.22 9.24 22.41 18.00 22.92 20.33 16.23 23.89 23.81 13.15
#> 104 186 178 144 1 120 27 34 126 98 112 137 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 141 198 62 198.1 53 44 65 118 119.1 19 156 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 94 119.2 196 72 151 87 2 135 122.1 176 62.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 2.1 103.1 186.2 119.3 71 152 33 31 121 80 21 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 112.1 186.3 191 46 142 28 173 46.1 200 193 174 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 75 119.4 198.2 137.2 176.1 12 109 12.1 152.1 141.1 141.2 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 9 126.1 200.1 121.1 200.2 165 75.1 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[86]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01325527 0.45684204 0.56502194
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.769762652 0.009424454 0.507117288
#> grade_iii, Cure model
#> 0.745543912
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 85 16.44 1 36 0 0
#> 181 16.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 127 3.53 1 62 0 1
#> 171 16.57 1 41 0 1
#> 25 6.32 1 34 1 0
#> 181.1 16.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 187.1 9.92 1 39 1 0
#> 88 18.37 1 47 0 0
#> 29 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 32 20.90 1 37 1 0
#> 81 14.06 1 34 0 0
#> 164.1 23.60 1 76 0 1
#> 113 22.86 1 34 0 0
#> 158 20.14 1 74 1 0
#> 29.1 15.45 1 68 1 0
#> 107 11.18 1 54 1 0
#> 177 12.53 1 75 0 0
#> 187.2 9.92 1 39 1 0
#> 114 13.68 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 26 15.77 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 85.1 16.44 1 36 0 0
#> 5 16.43 1 51 0 1
#> 113.1 22.86 1 34 0 0
#> 181.2 16.46 1 45 0 1
#> 25.1 6.32 1 34 1 0
#> 4 17.64 1 NA 0 1
#> 90 20.94 1 50 0 1
#> 61 10.12 1 36 0 1
#> 59 10.16 1 NA 1 0
#> 85.2 16.44 1 36 0 0
#> 88.1 18.37 1 47 0 0
#> 26.1 15.77 1 49 0 1
#> 45.1 17.42 1 54 0 1
#> 140 12.68 1 59 1 0
#> 169 22.41 1 46 0 0
#> 133 14.65 1 57 0 0
#> 108 18.29 1 39 0 1
#> 97 19.14 1 65 0 1
#> 36 21.19 1 48 0 1
#> 129.1 23.41 1 53 1 0
#> 97.1 19.14 1 65 0 1
#> 155 13.08 1 26 0 0
#> 37 12.52 1 57 1 0
#> 93 10.33 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 57 14.46 1 45 0 1
#> 179 18.63 1 42 0 0
#> 101 9.97 1 10 0 1
#> 184.1 17.77 1 38 0 0
#> 15 22.68 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 123 13.00 1 44 1 0
#> 175 21.91 1 43 0 0
#> 57.1 14.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 40 18.00 1 28 1 0
#> 4.1 17.64 1 NA 0 1
#> 195 11.76 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 183 9.24 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 89.1 11.44 1 NA 0 0
#> 145 10.07 1 65 1 0
#> 91 5.33 1 61 0 1
#> 63 22.77 1 31 1 0
#> 170 19.54 1 43 0 1
#> 32.1 20.90 1 37 1 0
#> 199.1 19.81 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 175.1 21.91 1 43 0 0
#> 30 17.43 1 78 0 0
#> 41 18.02 1 40 1 0
#> 43 12.10 1 61 0 1
#> 127.1 3.53 1 62 0 1
#> 39 15.59 1 37 0 1
#> 190 20.81 1 42 1 0
#> 139 21.49 1 63 1 0
#> 43.1 12.10 1 61 0 1
#> 4.2 17.64 1 NA 0 1
#> 136 21.83 1 43 0 1
#> 149 8.37 1 33 1 0
#> 43.2 12.10 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 81.1 14.06 1 34 0 0
#> 70 7.38 1 30 1 0
#> 85.3 16.44 1 36 0 0
#> 129.2 23.41 1 53 1 0
#> 111 17.45 1 47 0 1
#> 101.1 9.97 1 10 0 1
#> 51 18.23 1 83 0 1
#> 96 14.54 1 33 0 1
#> 93.1 10.33 1 52 0 1
#> 125.1 15.65 1 67 1 0
#> 154 12.63 1 20 1 0
#> 114.1 13.68 1 NA 0 0
#> 45.2 17.42 1 54 0 1
#> 68 20.62 1 44 0 0
#> 145.1 10.07 1 65 1 0
#> 5.1 16.43 1 51 0 1
#> 189.2 10.51 1 NA 1 0
#> 46 24.00 0 71 0 0
#> 185 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 160 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 152.1 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 34 24.00 0 36 0 0
#> 64 24.00 0 43 0 0
#> 112 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 161 24.00 0 45 0 0
#> 83 24.00 0 6 0 0
#> 120 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 120.1 24.00 0 68 0 1
#> 95 24.00 0 68 0 1
#> 143.1 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 11 24.00 0 42 0 1
#> 193 24.00 0 45 0 1
#> 28 24.00 0 67 1 0
#> 31 24.00 0 36 0 1
#> 12.1 24.00 0 63 0 0
#> 152.2 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 112.1 24.00 0 61 0 0
#> 109 24.00 0 48 0 0
#> 137.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 152.3 24.00 0 36 0 1
#> 116 24.00 0 58 0 1
#> 102.1 24.00 0 49 0 0
#> 11.1 24.00 0 42 0 1
#> 27 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 141 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 7 24.00 0 37 1 0
#> 138 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 94 24.00 0 51 0 1
#> 31.1 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 196.1 24.00 0 19 0 0
#> 75.1 24.00 0 21 1 0
#> 165 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 47 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 33.1 24.00 0 53 0 0
#> 160.1 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 84 24.00 0 39 0 1
#> 122.1 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 34.1 24.00 0 36 0 0
#> 200 24.00 0 64 0 0
#> 138.1 24.00 0 44 1 0
#> 160.2 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 46.1 24.00 0 71 0 0
#> 196.2 24.00 0 19 0 0
#> 98 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 21 24.00 0 47 0 0
#> 87 24.00 0 27 0 0
#> 186 24.00 0 45 1 0
#> 48.1 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 200.1 24.00 0 64 0 0
#> 173.1 24.00 0 19 0 1
#> 112.2 24.00 0 61 0 0
#> 126.1 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.770 NA NA NA
#> 2 age, Cure model 0.00942 NA NA NA
#> 3 grade_ii, Cure model 0.507 NA NA NA
#> 4 grade_iii, Cure model 0.746 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0133 NA NA NA
#> 2 grade_ii, Survival model 0.457 NA NA NA
#> 3 grade_iii, Survival model 0.565 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.769763 0.009424 0.507117 0.745544
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253.2
#> Residual Deviance: 247.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.769762652 0.009424454 0.507117288 0.745543912
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01325527 0.45684204 0.56502194
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4030243790 0.3709977200 0.2753880644 0.9743960738 0.3600301567
#> [6] 0.9362080648 0.3709977200 0.8602008608 0.8602008608 0.2149830437
#> [11] 0.5269602126 0.0139737413 0.0048481075 0.3280991319 0.1175751607
#> [16] 0.5979431310 0.0048481075 0.0344151864 0.1598075873 0.5269602126
#> [21] 0.7456501647 0.6708615322 0.8602008608 0.2960227517 0.4695143357
#> [26] 0.4922240488 0.4030243790 0.4468934605 0.0344151864 0.3709977200
#> [31] 0.9362080648 0.1090113227 0.7965547195 0.4030243790 0.2149830437
#> [36] 0.4695143357 0.3280991319 0.6463488483 0.0607178986 0.5503766817
#> [41] 0.2346771683 0.1779478335 0.1005099834 0.0139737413 0.1779478335
#> [46] 0.6219447379 0.6832359163 0.7711492780 0.6956684498 0.5742861233
#> [51] 0.1960919493 0.8349806405 0.2753880644 0.0536085010 0.1960919493
#> [56] 0.6341328516 0.0682293797 0.5742861233 0.7583897398 0.2651787835
#> [61] 0.0009265892 0.8978486665 0.8093415071 0.9615856518 0.0469174516
#> [66] 0.1688764482 0.1175751607 0.0283727221 0.0682293797 0.3172439700
#> [71] 0.2549342667 0.7082240754 0.9743960738 0.5153069589 0.1341597383
#> [76] 0.0920581892 0.7082240754 0.0838442452 0.9106410746 0.7082240754
#> [81] 0.1341597383 0.5979431310 0.9234299631 0.4030243790 0.0139737413
#> [86] 0.3066230025 0.8349806405 0.2447188411 0.5623486908 0.7711492780
#> [91] 0.4922240488 0.6586292883 0.3280991319 0.1509439681 0.8093415071
#> [96] 0.4468934605 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 85 181 184 127 171 25 181.1 187 187.1 88 29 129 164
#> 16.44 16.46 17.77 3.53 16.57 6.32 16.46 9.92 9.92 18.37 15.45 23.41 23.60
#> 45 32 81 164.1 113 158 29.1 107 177 187.2 110 26 125
#> 17.42 20.90 14.06 23.60 22.86 20.14 15.45 11.18 12.53 9.92 17.56 15.77 15.65
#> 85.1 5 113.1 181.2 25.1 90 61 85.2 88.1 26.1 45.1 140 169
#> 16.44 16.43 22.86 16.46 6.32 20.94 10.12 16.44 18.37 15.77 17.42 12.68 22.41
#> 133 108 97 36 129.1 97.1 155 37 93 56 57 179 101
#> 14.65 18.29 19.14 21.19 23.41 19.14 13.08 12.52 10.33 12.21 14.46 18.63 9.97
#> 184.1 15 179.1 123 175 57.1 159 40 24 183 145 91 63
#> 17.77 22.68 18.63 13.00 21.91 14.46 10.55 18.00 23.89 9.24 10.07 5.33 22.77
#> 170 32.1 92 175.1 30 41 43 127.1 39 190 139 43.1 136
#> 19.54 20.90 22.92 21.91 17.43 18.02 12.10 3.53 15.59 20.81 21.49 12.10 21.83
#> 149 43.2 190.1 81.1 70 85.3 129.2 111 101.1 51 96 93.1 125.1
#> 8.37 12.10 20.81 14.06 7.38 16.44 23.41 17.45 9.97 18.23 14.54 10.33 15.65
#> 154 45.2 68 145.1 5.1 46 185 146 126 74 152 137 143
#> 12.63 17.42 20.62 10.07 16.43 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 160 172 152.1 71 12 34 64 112 103 161 83 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 120.1 95 143.1 75 11 193 28 31 12.1 152.2 198 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 137.1 48 152.3 116 102.1 11.1 27 135 141 119 7 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 196 94 31.1 178 191 196.1 75.1 165 122 72 47 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 148 33.1 160.1 144 84 122.1 65 104 34.1 200 138.1 160.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 46.1 196.2 98 173 21 87 186 48.1 198.1 200.1 173.1 112.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[87]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.02088868 0.49917929 0.14192446
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.233576588 0.007544065 0.039568292
#> grade_iii, Cure model
#> 0.309030949
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 69 23.23 1 25 0 1
#> 140 12.68 1 59 1 0
#> 37 12.52 1 57 1 0
#> 63 22.77 1 31 1 0
#> 68 20.62 1 44 0 0
#> 8 18.43 1 32 0 0
#> 29 15.45 1 68 1 0
#> 96 14.54 1 33 0 1
#> 56 12.21 1 60 0 0
#> 49 12.19 1 48 1 0
#> 52 10.42 1 52 0 1
#> 190 20.81 1 42 1 0
#> 81 14.06 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 69.1 23.23 1 25 0 1
#> 92 22.92 1 47 0 1
#> 187 9.92 1 39 1 0
#> 110 17.56 1 65 0 1
#> 136 21.83 1 43 0 1
#> 188 16.16 1 46 0 1
#> 58 19.34 1 39 0 0
#> 167 15.55 1 56 1 0
#> 107 11.18 1 54 1 0
#> 97 19.14 1 65 0 1
#> 78 23.88 1 43 0 0
#> 155 13.08 1 26 0 0
#> 8.1 18.43 1 32 0 0
#> 107.1 11.18 1 54 1 0
#> 91 5.33 1 61 0 1
#> 129 23.41 1 53 1 0
#> 166 19.98 1 48 0 0
#> 181 16.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 81.1 14.06 1 34 0 0
#> 6 15.64 1 39 0 0
#> 24 23.89 1 38 0 0
#> 134 17.81 1 47 1 0
#> 30 17.43 1 78 0 0
#> 93 10.33 1 52 0 1
#> 92.1 22.92 1 47 0 1
#> 81.2 14.06 1 34 0 0
#> 111 17.45 1 47 0 1
#> 136.1 21.83 1 43 0 1
#> 70 7.38 1 30 1 0
#> 190.1 20.81 1 42 1 0
#> 100 16.07 1 60 0 0
#> 79 16.23 1 54 1 0
#> 5 16.43 1 51 0 1
#> 170 19.54 1 43 0 1
#> 58.1 19.34 1 39 0 0
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 24.1 23.89 1 38 0 0
#> 167.1 15.55 1 56 1 0
#> 79.1 16.23 1 54 1 0
#> 92.2 22.92 1 47 0 1
#> 128 20.35 1 35 0 1
#> 106 16.67 1 49 1 0
#> 99 21.19 1 38 0 1
#> 140.1 12.68 1 59 1 0
#> 86.1 23.81 1 58 0 1
#> 66 22.13 1 53 0 0
#> 181.1 16.46 1 45 0 1
#> 134.1 17.81 1 47 1 0
#> 42 12.43 1 49 0 1
#> 55 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 106.1 16.67 1 49 1 0
#> 171 16.57 1 41 0 1
#> 139 21.49 1 63 1 0
#> 58.2 19.34 1 39 0 0
#> 179 18.63 1 42 0 0
#> 93.1 10.33 1 52 0 1
#> 91.1 5.33 1 61 0 1
#> 58.3 19.34 1 39 0 0
#> 49.1 12.19 1 48 1 0
#> 111.1 17.45 1 47 0 1
#> 42.1 12.43 1 49 0 1
#> 153 21.33 1 55 1 0
#> 5.1 16.43 1 51 0 1
#> 78.1 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 66.1 22.13 1 53 0 0
#> 187.1 9.92 1 39 1 0
#> 190.2 20.81 1 42 1 0
#> 140.2 12.68 1 59 1 0
#> 177 12.53 1 75 0 0
#> 190.3 20.81 1 42 1 0
#> 69.2 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 108 18.29 1 39 0 1
#> 171.1 16.57 1 41 0 1
#> 128.1 20.35 1 35 0 1
#> 37.1 12.52 1 57 1 0
#> 30.1 17.43 1 78 0 0
#> 13 14.34 1 54 0 1
#> 127 3.53 1 62 0 1
#> 30.2 17.43 1 78 0 0
#> 69.3 23.23 1 25 0 1
#> 100.1 16.07 1 60 0 0
#> 133 14.65 1 57 0 0
#> 187.2 9.92 1 39 1 0
#> 63.1 22.77 1 31 1 0
#> 177.1 12.53 1 75 0 0
#> 29.1 15.45 1 68 1 0
#> 108.1 18.29 1 39 0 1
#> 149 8.37 1 33 1 0
#> 41 18.02 1 40 1 0
#> 32 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 30.3 17.43 1 78 0 0
#> 7 24.00 0 37 1 0
#> 146 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 9 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 198 24.00 0 66 0 1
#> 64 24.00 0 43 0 0
#> 21 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 198.1 24.00 0 66 0 1
#> 31 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 31.1 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 178 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 115 24.00 0 NA 1 0
#> 17 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 126 24.00 0 48 0 0
#> 198.2 24.00 0 66 0 1
#> 19 24.00 0 57 0 1
#> 3 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 198.3 24.00 0 66 0 1
#> 3.1 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 31.2 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 178.1 24.00 0 52 1 0
#> 122.1 24.00 0 66 0 0
#> 95.1 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 38 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 33 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 186 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 120 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 53 24.00 0 32 0 1
#> 119.1 24.00 0 17 0 0
#> 62 24.00 0 71 0 0
#> 121.1 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 173.1 24.00 0 19 0 1
#> 200 24.00 0 64 0 0
#> 102 24.00 0 49 0 0
#> 71.1 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 82 24.00 0 34 0 0
#> 138 24.00 0 44 1 0
#> 62.1 24.00 0 71 0 0
#> 121.2 24.00 0 57 1 0
#> 173.2 24.00 0 19 0 1
#> 173.3 24.00 0 19 0 1
#> 38.1 24.00 0 31 1 0
#> 173.4 24.00 0 19 0 1
#> 35 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 82.1 24.00 0 34 0 0
#> 75 24.00 0 21 1 0
#> 152 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 103.1 24.00 0 56 1 0
#> 178.2 24.00 0 52 1 0
#> 82.2 24.00 0 34 0 0
#> 94 24.00 0 51 0 1
#> 31.3 24.00 0 36 0 1
#> 135 24.00 0 58 1 0
#> 65 24.00 0 57 1 0
#> 173.5 24.00 0 19 0 1
#> 152.1 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 120.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.234 NA NA NA
#> 2 age, Cure model 0.00754 NA NA NA
#> 3 grade_ii, Cure model 0.0396 NA NA NA
#> 4 grade_iii, Cure model 0.309 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0209 NA NA NA
#> 2 grade_ii, Survival model 0.499 NA NA NA
#> 3 grade_iii, Survival model 0.142 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.233577 0.007544 0.039568 0.309031
#>
#> Degrees of Freedom: 197 Total (i.e. Null); 194 Residual
#> Null Deviance: 271.6
#> Residual Deviance: 270.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.233576588 0.007544065 0.039568292 0.309030949
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.02088868 0.49917929 0.14192446
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3685388 0.4335487 0.9287566 0.9438248 0.5353380 0.6745415 0.7592381
#> [8] 0.8963091 0.9062300 0.9553168 0.9581536 0.9691274 0.6462948 0.9127543
#> [15] 0.4335487 0.4957603 0.9797628 0.8005457 0.5816681 0.8749040 0.7203300
#> [22] 0.8893828 0.9637044 0.7482480 0.2974578 0.9223556 0.7592381 0.9637044
#> [29] 0.9925322 0.4143341 0.7016979 0.8519515 0.9255592 0.9127543 0.8857922
#> [36] 0.1892626 0.7907852 0.8146670 0.9718245 0.4957603 0.9127543 0.8053390
#> [43] 0.5816681 0.9899943 0.6462948 0.8785888 0.8674871 0.8598016 0.7142301
#> [50] 0.7203300 0.7856748 0.8479452 0.1892626 0.8893828 0.8674871 0.4957603
#> [57] 0.6816036 0.8316325 0.6210348 0.9287566 0.3685388 0.5594726 0.8519515
#> [64] 0.7907852 0.9496091 0.7203300 0.9771400 0.8316325 0.8398567 0.6024155
#> [71] 0.7203300 0.7537712 0.9718245 0.9925322 0.7203300 0.9581536 0.8053390
#> [78] 0.9496091 0.6120220 0.8598016 0.2974578 0.6952622 0.5594726 0.9797628
#> [85] 0.6462948 0.9287566 0.9378794 0.6462948 0.4335487 0.6210348 0.7699859
#> [92] 0.8398567 0.6816036 0.9438248 0.8146670 0.9095072 0.9975219 0.8146670
#> [99] 0.4335487 0.8785888 0.9029375 0.9797628 0.5353380 0.9378794 0.8963091
#> [106] 0.7699859 0.9874428 0.7804986 0.6380263 0.7080334 0.8146670 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [197] 0.0000000 0.0000000
#>
#> $Time
#> 86 69 140 37 63 68 8 29 96 56 49 52 190
#> 23.81 23.23 12.68 12.52 22.77 20.62 18.43 15.45 14.54 12.21 12.19 10.42 20.81
#> 81 69.1 92 187 110 136 188 58 167 107 97 78 155
#> 14.06 23.23 22.92 9.92 17.56 21.83 16.16 19.34 15.55 11.18 19.14 23.88 13.08
#> 8.1 107.1 91 129 166 181 14 81.1 6 24 134 30 93
#> 18.43 11.18 5.33 23.41 19.98 16.46 12.89 14.06 15.64 23.89 17.81 17.43 10.33
#> 92.1 81.2 111 136.1 70 190.1 100 79 5 170 58.1 40 130
#> 22.92 14.06 17.45 21.83 7.38 20.81 16.07 16.23 16.43 19.54 19.34 18.00 16.47
#> 24.1 167.1 79.1 92.2 128 106 99 140.1 86.1 66 181.1 134.1 42
#> 23.89 15.55 16.23 22.92 20.35 16.67 21.19 12.68 23.81 22.13 16.46 17.81 12.43
#> 55 145 106.1 171 139 58.2 179 93.1 91.1 58.3 49.1 111.1 42.1
#> 19.34 10.07 16.67 16.57 21.49 19.34 18.63 10.33 5.33 19.34 12.19 17.45 12.43
#> 153 5.1 78.1 158 66.1 187.1 190.2 140.2 177 190.3 69.2 36 108
#> 21.33 16.43 23.88 20.14 22.13 9.92 20.81 12.68 12.53 20.81 23.23 21.19 18.29
#> 171.1 128.1 37.1 30.1 13 127 30.2 69.3 100.1 133 187.2 63.1 177.1
#> 16.57 20.35 12.52 17.43 14.34 3.53 17.43 23.23 16.07 14.65 9.92 22.77 12.53
#> 29.1 108.1 149 41 32 105 30.3 7 146 54 9 148 198
#> 15.45 18.29 8.37 18.02 20.90 19.75 17.43 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 21 146.1 198.1 31 141 31.1 162 46 71 137 178 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 17 104 121 47 126 198.2 19 3 143 198.3 3.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 31.2 95 147 178.1 122.1 95.1 119 38 46.1 142 33 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 2 120 112 53 119.1 62 121.1 116 173.1 200 102 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 82 138 62.1 121.2 173.2 173.3 38.1 173.4 35 48 48.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 82.1 75 152 103 103.1 178.2 82.2 94 31.3 135 65 173.5
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 163 120.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[88]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004405359 0.860671835 0.044867785
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.51577922 0.00854293 0.29971567
#> grade_iii, Cure model
#> 0.63044505
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 69 23.23 1 25 0 1
#> 26 15.77 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 181 16.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 85 16.44 1 36 0 0
#> 69.1 23.23 1 25 0 1
#> 8 18.43 1 32 0 0
#> 139 21.49 1 63 1 0
#> 14 12.89 1 21 0 0
#> 99 21.19 1 38 0 1
#> 140 12.68 1 59 1 0
#> 183 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 8.1 18.43 1 32 0 0
#> 194 22.40 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 8.2 18.43 1 32 0 0
#> 164 23.60 1 76 0 1
#> 155 13.08 1 26 0 0
#> 25 6.32 1 34 1 0
#> 153 21.33 1 55 1 0
#> 199 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 6 15.64 1 39 0 0
#> 79 16.23 1 54 1 0
#> 190 20.81 1 42 1 0
#> 145 10.07 1 65 1 0
#> 36 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 25.1 6.32 1 34 1 0
#> 105 19.75 1 60 0 0
#> 89 11.44 1 NA 0 0
#> 25.2 6.32 1 34 1 0
#> 188 16.16 1 46 0 1
#> 180 14.82 1 37 0 0
#> 100 16.07 1 60 0 0
#> 15 22.68 1 48 0 0
#> 123 13.00 1 44 1 0
#> 180.1 14.82 1 37 0 0
#> 91 5.33 1 61 0 1
#> 127 3.53 1 62 0 1
#> 90 20.94 1 50 0 1
#> 130 16.47 1 53 0 1
#> 60 13.15 1 38 1 0
#> 113 22.86 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 90.2 20.94 1 50 0 1
#> 164.1 23.60 1 76 0 1
#> 42 12.43 1 49 0 1
#> 159 10.55 1 50 0 1
#> 180.2 14.82 1 37 0 0
#> 100.1 16.07 1 60 0 0
#> 188.1 16.16 1 46 0 1
#> 197 21.60 1 69 1 0
#> 175 21.91 1 43 0 0
#> 32 20.90 1 37 1 0
#> 139.1 21.49 1 63 1 0
#> 136 21.83 1 43 0 1
#> 194.1 22.40 1 38 0 1
#> 183.1 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 6.1 15.64 1 39 0 0
#> 168 23.72 1 70 0 0
#> 167 15.55 1 56 1 0
#> 190.1 20.81 1 42 1 0
#> 110 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 171.1 16.57 1 41 0 1
#> 106 16.67 1 49 1 0
#> 61 10.12 1 36 0 1
#> 154 12.63 1 20 1 0
#> 117 17.46 1 26 0 1
#> 55 19.34 1 69 0 1
#> 45 17.42 1 54 0 1
#> 100.2 16.07 1 60 0 0
#> 170 19.54 1 43 0 1
#> 110.1 17.56 1 65 0 1
#> 157 15.10 1 47 0 0
#> 111 17.45 1 47 0 1
#> 133 14.65 1 57 0 0
#> 190.2 20.81 1 42 1 0
#> 124 9.73 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 29 15.45 1 68 1 0
#> 184 17.77 1 38 0 0
#> 136.1 21.83 1 43 0 1
#> 183.2 9.24 1 67 1 0
#> 18 15.21 1 49 1 0
#> 30 17.43 1 78 0 0
#> 188.2 16.16 1 46 0 1
#> 30.1 17.43 1 78 0 0
#> 140.1 12.68 1 59 1 0
#> 187 9.92 1 39 1 0
#> 45.1 17.42 1 54 0 1
#> 114.1 13.68 1 NA 0 0
#> 18.1 15.21 1 49 1 0
#> 140.2 12.68 1 59 1 0
#> 88 18.37 1 47 0 0
#> 61.1 10.12 1 36 0 1
#> 90.3 20.94 1 50 0 1
#> 140.3 12.68 1 59 1 0
#> 159.1 10.55 1 50 0 1
#> 133.1 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 169 22.41 1 46 0 0
#> 145.1 10.07 1 65 1 0
#> 37 12.52 1 57 1 0
#> 15.1 22.68 1 48 0 0
#> 194.2 22.40 1 38 0 1
#> 13 14.34 1 54 0 1
#> 141 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 163 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 64 24.00 0 43 0 0
#> 74.1 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 182 24.00 0 35 0 0
#> 48 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 132 24.00 0 55 0 0
#> 185 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 35 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 27 24.00 0 63 1 0
#> 135.1 24.00 0 58 1 0
#> 53 24.00 0 32 0 1
#> 87 24.00 0 27 0 0
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#> 20 24.00 0 46 1 0
#> 148 24.00 0 61 1 0
#> 147 24.00 0 76 1 0
#> 35.1 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 112.2 24.00 0 61 0 0
#> 163.1 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 126 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 198 24.00 0 66 0 1
#> 72 24.00 0 40 0 1
#> 84.1 24.00 0 39 0 1
#> 191 24.00 0 60 0 1
#> 46 24.00 0 71 0 0
#> 178 24.00 0 52 1 0
#> 53.1 24.00 0 32 0 1
#> 182.1 24.00 0 35 0 0
#> 33.1 24.00 0 53 0 0
#> 1 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 74.2 24.00 0 43 0 1
#> 198.1 24.00 0 66 0 1
#> 135.2 24.00 0 58 1 0
#> 152 24.00 0 36 0 1
#> 35.2 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 35.3 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 35.4 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 193 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 135.3 24.00 0 58 1 0
#> 53.2 24.00 0 32 0 1
#> 38 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 33.2 24.00 0 53 0 0
#> 126.1 24.00 0 48 0 0
#> 131.1 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 1.1 24.00 0 23 1 0
#> 144 24.00 0 28 0 1
#> 7.1 24.00 0 37 1 0
#> 44 24.00 0 56 0 0
#> 83 24.00 0 6 0 0
#> 118 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 137.1 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 7.2 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 141.1 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.516 NA NA NA
#> 2 age, Cure model 0.00854 NA NA NA
#> 3 grade_ii, Cure model 0.300 NA NA NA
#> 4 grade_iii, Cure model 0.630 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00441 NA NA NA
#> 2 grade_ii, Survival model 0.861 NA NA NA
#> 3 grade_iii, Survival model 0.0449 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.515779 0.008543 0.299716 0.630445
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 263.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51577922 0.00854293 0.29971567 0.63044505
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004405359 0.860671835 0.044867785
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.038845352 0.630057798 0.535407717 0.317880638 0.545152125 0.038845352
#> [7] 0.373294299 0.191441560 0.788569525 0.222073856 0.797736512 0.935379170
#> [13] 0.545152125 0.373294299 0.111878388 0.373294299 0.020200619 0.770151213
#> [19] 0.959944296 0.211974877 0.363943816 0.639686800 0.564158375 0.291390802
#> [25] 0.910010950 0.222073856 0.884208967 0.959944296 0.336157817 0.959944296
#> [31] 0.573604255 0.705450849 0.601677148 0.078699967 0.779411946 0.705450849
#> [37] 0.983875168 0.991930897 0.242052223 0.525688465 0.760902516 0.058269385
#> [43] 0.242052223 0.242052223 0.020200619 0.849847234 0.867082941 0.705450849
#> [49] 0.601677148 0.573604255 0.179875383 0.144441224 0.281372398 0.191441560
#> [55] 0.156400684 0.111878388 0.935379170 0.326994882 0.058269385 0.639686800
#> [61] 0.010649756 0.658890475 0.291390802 0.419887268 0.506490111 0.506490111
#> [67] 0.496845104 0.892825516 0.832484920 0.438859641 0.354633748 0.477403912
#> [73] 0.601677148 0.345379147 0.419887268 0.696210190 0.448464765 0.732971939
#> [79] 0.291390802 0.858504622 0.668444415 0.410384682 0.156400684 0.935379170
#> [85] 0.677896681 0.458100795 0.573604255 0.458100795 0.797736512 0.926948214
#> [91] 0.477403912 0.677896681 0.797736512 0.400915901 0.892825516 0.242052223
#> [97] 0.797736512 0.867082941 0.732971939 0.003180301 0.100222757 0.910010950
#> [103] 0.841203687 0.078699967 0.111878388 0.751539994 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 69 26 181 128 85 69.1 8 139 14 99 140 183 192
#> 23.23 15.77 16.46 20.35 16.44 23.23 18.43 21.49 12.89 21.19 12.68 9.24 16.44
#> 8.1 194 8.2 164 155 25 153 179 6 79 190 145 36
#> 18.43 22.40 18.43 23.60 13.08 6.32 21.33 18.63 15.64 16.23 20.81 10.07 21.19
#> 10 25.1 105 25.2 188 180 100 15 123 180.1 91 127 90
#> 10.53 6.32 19.75 6.32 16.16 14.82 16.07 22.68 13.00 14.82 5.33 3.53 20.94
#> 130 60 113 90.1 90.2 164.1 42 159 180.2 100.1 188.1 197 175
#> 16.47 13.15 22.86 20.94 20.94 23.60 12.43 10.55 14.82 16.07 16.16 21.60 21.91
#> 32 139.1 136 194.1 183.1 150 113.1 6.1 168 167 190.1 110 171
#> 20.90 21.49 21.83 22.40 9.24 20.33 22.86 15.64 23.72 15.55 20.81 17.56 16.57
#> 171.1 106 61 154 117 55 45 100.2 170 110.1 157 111 133
#> 16.57 16.67 10.12 12.63 17.46 19.34 17.42 16.07 19.54 17.56 15.10 17.45 14.65
#> 190.2 49 29 184 136.1 183.2 18 30 188.2 30.1 140.1 187 45.1
#> 20.81 12.19 15.45 17.77 21.83 9.24 15.21 17.43 16.16 17.43 12.68 9.92 17.42
#> 18.1 140.2 88 61.1 90.3 140.3 159.1 133.1 78 169 145.1 37 15.1
#> 15.21 12.68 18.37 10.12 20.94 12.68 10.55 14.65 23.88 22.41 10.07 12.52 22.68
#> 194.2 13 141 74 173 163 131 186 33 137 112 64 74.1
#> 22.40 14.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 182 48 112.1 132 185 80 35 65 135 27 135.1 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 174 9 87.1 20 148 147 35.1 156 112.2 163.1 84 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 198 72 84.1 191 46 178 53.1 182.1 33.1 1 119 74.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 135.2 152 35.2 47 35.3 7 142 35.4 116 193 94 135.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.2 38 176 33.2 126.1 131.1 143 161 1.1 144 7.1 44 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 144.1 82 137.1 120 120.1 7.2 71 94.1 141.1 46.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[89]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007467552 0.351419883 0.328985358
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.94537859 0.01598001 0.22587104
#> grade_iii, Cure model
#> 0.76640084
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 5 16.43 1 51 0 1
#> 85 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 129 23.41 1 53 1 0
#> 45 17.42 1 54 0 1
#> 85.1 16.44 1 36 0 0
#> 105 19.75 1 60 0 0
#> 14 12.89 1 21 0 0
#> 114 13.68 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 41 18.02 1 40 1 0
#> 139 21.49 1 63 1 0
#> 86 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 24 23.89 1 38 0 0
#> 55 19.34 1 69 0 1
#> 26 15.77 1 49 0 1
#> 123 13.00 1 44 1 0
#> 99 21.19 1 38 0 1
#> 150.1 20.33 1 48 0 0
#> 8 18.43 1 32 0 0
#> 43 12.10 1 61 0 1
#> 88 18.37 1 47 0 0
#> 180 14.82 1 37 0 0
#> 49 12.19 1 48 1 0
#> 101 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 18 15.21 1 49 1 0
#> 37 12.52 1 57 1 0
#> 192.1 16.44 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 197 21.60 1 69 1 0
#> 139.1 21.49 1 63 1 0
#> 92 22.92 1 47 0 1
#> 181 16.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 197.1 21.60 1 69 1 0
#> 195 11.76 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 4.2 17.64 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 30 17.43 1 78 0 0
#> 177 12.53 1 75 0 0
#> 18.1 15.21 1 49 1 0
#> 4.3 17.64 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 130.1 16.47 1 53 0 1
#> 52 10.42 1 52 0 1
#> 166 19.98 1 48 0 0
#> 140 12.68 1 59 1 0
#> 70 7.38 1 30 1 0
#> 180.1 14.82 1 37 0 0
#> 43.1 12.10 1 61 0 1
#> 177.1 12.53 1 75 0 0
#> 18.2 15.21 1 49 1 0
#> 170 19.54 1 43 0 1
#> 124 9.73 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 187 9.92 1 39 1 0
#> 167 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 195.1 11.76 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 50.2 10.02 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 4.4 17.64 1 NA 0 1
#> 129.1 23.41 1 53 1 0
#> 155 13.08 1 26 0 0
#> 70.1 7.38 1 30 1 0
#> 41.1 18.02 1 40 1 0
#> 29 15.45 1 68 1 0
#> 16.1 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 39 15.59 1 37 0 1
#> 89 11.44 1 NA 0 0
#> 168 23.72 1 70 0 0
#> 117 17.46 1 26 0 1
#> 58 19.34 1 39 0 0
#> 145 10.07 1 65 1 0
#> 36.1 21.19 1 48 0 1
#> 155.1 13.08 1 26 0 0
#> 13.1 14.34 1 54 0 1
#> 166.1 19.98 1 48 0 0
#> 134 17.81 1 47 1 0
#> 179 18.63 1 42 0 0
#> 6 15.64 1 39 0 0
#> 59 10.16 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 88.1 18.37 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 153.2 21.33 1 55 1 0
#> 51 18.23 1 83 0 1
#> 49.1 12.19 1 48 1 0
#> 111 17.45 1 47 0 1
#> 168.1 23.72 1 70 0 0
#> 108 18.29 1 39 0 1
#> 100 16.07 1 60 0 0
#> 85.2 16.44 1 36 0 0
#> 45.1 17.42 1 54 0 1
#> 15 22.68 1 48 0 0
#> 97 19.14 1 65 0 1
#> 194 22.40 1 38 0 1
#> 78 23.88 1 43 0 0
#> 85.3 16.44 1 36 0 0
#> 26.1 15.77 1 49 0 1
#> 109 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 120 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 17 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 17.1 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 17.2 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 11 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 62.1 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 173.1 24.00 0 19 0 1
#> 87.1 24.00 0 27 0 0
#> 67 24.00 0 25 0 0
#> 141 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 35 24.00 0 51 0 0
#> 109.1 24.00 0 48 0 0
#> 62.2 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 176 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 142 24.00 0 53 0 0
#> 27 24.00 0 63 1 0
#> 87.2 24.00 0 27 0 0
#> 71.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 174 24.00 0 49 1 0
#> 135 24.00 0 58 1 0
#> 38 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 87.3 24.00 0 27 0 0
#> 82.1 24.00 0 34 0 0
#> 67.1 24.00 0 25 0 0
#> 143.1 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 64 24.00 0 43 0 0
#> 20.1 24.00 0 46 1 0
#> 176.1 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 143.2 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 160 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 174.1 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 11.1 24.00 0 42 0 1
#> 22 24.00 0 52 1 0
#> 173.2 24.00 0 19 0 1
#> 104 24.00 0 50 1 0
#> 148.1 24.00 0 61 1 0
#> 72.1 24.00 0 40 0 1
#> 198 24.00 0 66 0 1
#> 64.1 24.00 0 43 0 0
#> 95 24.00 0 68 0 1
#> 143.3 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 9.1 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 7 24.00 0 37 1 0
#> 132.1 24.00 0 55 0 0
#> 160.1 24.00 0 31 1 0
#> 109.2 24.00 0 48 0 0
#> 137 24.00 0 45 1 0
#> 141.1 24.00 0 44 1 0
#> 121.2 24.00 0 57 1 0
#> 115 24.00 0 NA 1 0
#> 65.1 24.00 0 57 1 0
#> 147 24.00 0 76 1 0
#> 116 24.00 0 58 0 1
#> 31.1 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.945 NA NA NA
#> 2 age, Cure model 0.0160 NA NA NA
#> 3 grade_ii, Cure model 0.226 NA NA NA
#> 4 grade_iii, Cure model 0.766 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00747 NA NA NA
#> 2 grade_ii, Survival model 0.351 NA NA NA
#> 3 grade_iii, Survival model 0.329 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94538 0.01598 0.22587 0.76640
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.8
#> Residual Deviance: 245.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94537859 0.01598001 0.22587104 0.76640084
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007467552 0.351419883 0.328985358
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.545480494 0.482307042 0.191258389 0.038570589 0.428006058 0.482307042
#> [7] 0.229691137 0.780627710 0.164331622 0.353316791 0.119082374 0.014457831
#> [13] 0.482307042 0.001947712 0.259597036 0.567735974 0.769242771 0.164331622
#> [19] 0.191258389 0.300412518 0.872579404 0.310889257 0.678985957 0.849574420
#> [25] 0.930557118 0.837995218 0.449634041 0.645798722 0.826421815 0.482307042
#> [31] 0.137432099 0.101049325 0.119082374 0.064609304 0.471329642 0.895656733
#> [37] 0.101049325 0.137432099 0.735303335 0.406456229 0.803459934 0.645798722
#> [43] 0.712793071 0.449634041 0.907278310 0.210209799 0.792036802 0.976917859
#> [49] 0.678985957 0.872579404 0.803459934 0.645798722 0.239805979 0.055565315
#> [55] 0.942163696 0.623329681 0.073682967 0.953761413 0.239805979 0.038570589
#> [61] 0.746633722 0.976917859 0.353316791 0.634549803 0.953761413 0.701473467
#> [67] 0.601117002 0.022010312 0.385125666 0.259597036 0.918908470 0.164331622
#> [73] 0.746633722 0.712793071 0.210209799 0.374420763 0.290012899 0.589883501
#> [79] 0.406456229 0.310889257 0.601117002 0.137432099 0.342567251 0.849574420
#> [85] 0.395787813 0.022010312 0.331902183 0.556568060 0.482307042 0.428006058
#> [91] 0.082617991 0.279712744 0.091854635 0.007350576 0.482307042 0.567735974
#> [97] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000
#>
#> $Time
#> 5 85 150 129 45 85.1 105 14 36 41 139 86 192
#> 16.43 16.44 20.33 23.41 17.42 16.44 19.75 12.89 21.19 18.02 21.49 23.81 16.44
#> 24 55 26 123 99 150.1 8 43 88 180 49 101 42
#> 23.89 19.34 15.77 13.00 21.19 20.33 18.43 12.10 18.37 14.82 12.19 9.97 12.43
#> 130 18 37 192.1 153 197 139.1 92 181 107 197.1 153.1 60
#> 16.47 15.21 12.52 16.44 21.33 21.60 21.49 22.92 16.46 11.18 21.60 21.33 13.15
#> 30 177 18.1 13 130.1 52 166 140 70 180.1 43.1 177.1 18.2
#> 17.43 12.53 15.21 14.34 16.47 10.42 19.98 12.68 7.38 14.82 12.10 12.53 15.21
#> 170 69 187 167 63 16 170.1 129.1 155 70.1 41.1 29 16.1
#> 19.54 23.23 9.92 15.55 22.77 8.71 19.54 23.41 13.08 7.38 18.02 15.45 8.71
#> 96 39 168 117 58 145 36.1 155.1 13.1 166.1 134 179 6
#> 14.54 15.59 23.72 17.46 19.34 10.07 21.19 13.08 14.34 19.98 17.81 18.63 15.64
#> 30.1 88.1 39.1 153.2 51 49.1 111 168.1 108 100 85.2 45.1 15
#> 17.43 18.37 15.59 21.33 18.23 12.19 17.45 23.72 18.29 16.07 16.44 17.42 22.68
#> 97 194 78 85.3 26.1 109 84 120 87 17 20 17.1 62
#> 19.14 22.40 23.88 16.44 15.77 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 119 17.2 173 11 80 28 62.1 72 173.1 87.1 67 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 126 102 35 109.1 62.2 132 148 176 82 142 27 87.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 83 174 135 38 161 143 178 87.3 82.1 67.1 143.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 176.1 131 9 143.2 191 160 121 65 174.1 165 31 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 173.2 104 148.1 72.1 198 64.1 95 143.3 48 121.1 9.1 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 132.1 160.1 109.2 137 141.1 121.2 65.1 147 116 31.1 162 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[90]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01331024 0.70057315 0.50261909
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.424912406 0.003019631 0.282689060
#> grade_iii, Cure model
#> 1.110840163
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 190 20.81 1 42 1 0
#> 13 14.34 1 54 0 1
#> 150 20.33 1 48 0 0
#> 125 15.65 1 67 1 0
#> 25 6.32 1 34 1 0
#> 188 16.16 1 46 0 1
#> 5 16.43 1 51 0 1
#> 149 8.37 1 33 1 0
#> 10 10.53 1 34 0 0
#> 140 12.68 1 59 1 0
#> 127 3.53 1 62 0 1
#> 25.1 6.32 1 34 1 0
#> 15 22.68 1 48 0 0
#> 25.2 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 199 19.81 1 NA 0 1
#> 192 16.44 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 168 23.72 1 70 0 0
#> 85 16.44 1 36 0 0
#> 145 10.07 1 65 1 0
#> 16 8.71 1 71 0 1
#> 45 17.42 1 54 0 1
#> 101 9.97 1 10 0 1
#> 49 12.19 1 48 1 0
#> 58.1 19.34 1 39 0 0
#> 128 20.35 1 35 0 1
#> 188.1 16.16 1 46 0 1
#> 97 19.14 1 65 0 1
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 26 15.77 1 49 0 1
#> 92 22.92 1 47 0 1
#> 99 21.19 1 38 0 1
#> 61 10.12 1 36 0 1
#> 40 18.00 1 28 1 0
#> 76 19.22 1 54 0 1
#> 88 18.37 1 47 0 0
#> 159 10.55 1 50 0 1
#> 41 18.02 1 40 1 0
#> 127.1 3.53 1 62 0 1
#> 159.1 10.55 1 50 0 1
#> 42 12.43 1 49 0 1
#> 14 12.89 1 21 0 0
#> 106 16.67 1 49 1 0
#> 139 21.49 1 63 1 0
#> 183 9.24 1 67 1 0
#> 40.1 18.00 1 28 1 0
#> 159.2 10.55 1 50 0 1
#> 58.2 19.34 1 39 0 0
#> 158 20.14 1 74 1 0
#> 168.1 23.72 1 70 0 0
#> 81 14.06 1 34 0 0
#> 108 18.29 1 39 0 1
#> 158.1 20.14 1 74 1 0
#> 166 19.98 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 93 10.33 1 52 0 1
#> 157 15.10 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 124.1 9.73 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 188.2 16.16 1 46 0 1
#> 15.1 22.68 1 48 0 0
#> 66 22.13 1 53 0 0
#> 4 17.64 1 NA 0 1
#> 192.1 16.44 1 31 1 0
#> 51 18.23 1 83 0 1
#> 96 14.54 1 33 0 1
#> 114.1 13.68 1 NA 0 0
#> 181.1 16.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 91 5.33 1 61 0 1
#> 150.1 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 91.1 5.33 1 61 0 1
#> 166.1 19.98 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 145.1 10.07 1 65 1 0
#> 23 16.92 1 61 0 0
#> 164.1 23.60 1 76 0 1
#> 183.2 9.24 1 67 1 0
#> 114.2 13.68 1 NA 0 0
#> 42.1 12.43 1 49 0 1
#> 99.1 21.19 1 38 0 1
#> 10.1 10.53 1 34 0 0
#> 96.1 14.54 1 33 0 1
#> 30 17.43 1 78 0 0
#> 96.2 14.54 1 33 0 1
#> 92.1 22.92 1 47 0 1
#> 190.1 20.81 1 42 1 0
#> 76.1 19.22 1 54 0 1
#> 63 22.77 1 31 1 0
#> 99.2 21.19 1 38 0 1
#> 167 15.55 1 56 1 0
#> 43 12.10 1 61 0 1
#> 123 13.00 1 44 1 0
#> 91.2 5.33 1 61 0 1
#> 105 19.75 1 60 0 0
#> 128.1 20.35 1 35 0 1
#> 5.1 16.43 1 51 0 1
#> 181.2 16.46 1 45 0 1
#> 195 11.76 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 184 17.77 1 38 0 0
#> 189 10.51 1 NA 1 0
#> 192.2 16.44 1 31 1 0
#> 10.2 10.53 1 34 0 0
#> 15.2 22.68 1 48 0 0
#> 111 17.45 1 47 0 1
#> 121 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 172 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 95 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 21 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#> 83 24.00 0 6 0 0
#> 122 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 185 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 1 24.00 0 23 1 0
#> 148 24.00 0 61 1 0
#> 172.1 24.00 0 41 0 0
#> 178 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 152 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 126 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 191 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 87.1 24.00 0 27 0 0
#> 11 24.00 0 42 0 1
#> 7.1 24.00 0 37 1 0
#> 118 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 152.1 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 112.1 24.00 0 61 0 0
#> 152.2 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 148.1 24.00 0 61 1 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 102.1 24.00 0 49 0 0
#> 160 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 9.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 9.2 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 146 24.00 0 63 1 0
#> 48.1 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 122.1 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 95.2 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 53.1 24.00 0 32 0 1
#> 200 24.00 0 64 0 0
#> 53.2 24.00 0 32 0 1
#> 103.1 24.00 0 56 1 0
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 143.1 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 196.1 24.00 0 19 0 0
#> 102.2 24.00 0 49 0 0
#> 64 24.00 0 43 0 0
#> 34 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 2 24.00 0 9 0 0
#> 131 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 87.2 24.00 0 27 0 0
#> 121.1 24.00 0 57 1 0
#> 54.1 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.425 NA NA NA
#> 2 age, Cure model 0.00302 NA NA NA
#> 3 grade_ii, Cure model 0.283 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0133 NA NA NA
#> 2 grade_ii, Survival model 0.701 NA NA NA
#> 3 grade_iii, Survival model 0.503 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.42491 0.00302 0.28269 1.11084
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 250.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.424912406 0.003019631 0.282689060 1.110840163
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01331024 0.70057315 0.50261909
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.1905784440 0.0998484725 0.5924800507 0.1306784709 0.5171989924
#> [6] 0.9114473795 0.4751792009 0.4542057010 0.9002258234 0.7445965653
#> [11] 0.6363526059 0.9775836267 0.9114473795 0.0334675737 0.9114473795
#> [16] 0.5495215786 0.4135237607 0.7775468489 0.0004668229 0.4135237607
#> [21] 0.8111078081 0.8889623366 0.3502457034 0.8334335068 0.6904101809
#> [26] 0.1905784440 0.1153004528 0.4751792009 0.2381371490 0.3821385545
#> [31] 0.6473776959 0.5065033538 0.0161526971 0.0770870893 0.7999141722
#> [36] 0.2994503729 0.2186589710 0.2482119875 0.7121687651 0.2890777633
#> [41] 0.9775836267 0.7121687651 0.6688458310 0.6253430166 0.3714599480
#> [46] 0.0686297508 0.8557467558 0.2994503729 0.7121687651 0.1905784440
#> [51] 0.1469624423 0.0004668229 0.6033941046 0.2584806914 0.1469624423
#> [56] 0.1637071344 0.2584806914 0.7887168210 0.5386771305 0.6473776959
#> [61] 0.4751792009 0.0334675737 0.0524548806 0.4135237607 0.2786365925
#> [66] 0.5604499004 0.3821385545 0.0603057300 0.9443614336 0.1306784709
#> [71] 0.0059124451 0.9443614336 0.1637071344 0.8557467558 0.8111078081
#> [76] 0.3607661279 0.0059124451 0.8557467558 0.6688458310 0.0770870893
#> [81] 0.7445965653 0.5604499004 0.3397863639 0.5604499004 0.0161526971
#> [86] 0.0998484725 0.2186589710 0.0275004291 0.0770870893 0.5279332725
#> [91] 0.7012670206 0.6143804948 0.9443614336 0.1813023874 0.1153004528
#> [96] 0.4542057010 0.3821385545 0.8446047921 0.3193123256 0.4135237607
#> [101] 0.7445965653 0.0334675737 0.3295309357 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 58 190 13 150 125 25 188 5 149 10 140 127 25.1
#> 19.34 20.81 14.34 20.33 15.65 6.32 16.16 16.43 8.37 10.53 12.68 3.53 6.32
#> 15 25.2 180 192 52 168 85 145 16 45 101 49 58.1
#> 22.68 6.32 14.82 16.44 10.42 23.72 16.44 10.07 8.71 17.42 9.97 12.19 19.34
#> 128 188.1 97 181 154 26 92 99 61 40 76 88 159
#> 20.35 16.16 19.14 16.46 12.63 15.77 22.92 21.19 10.12 18.00 19.22 18.37 10.55
#> 41 127.1 159.1 42 14 106 139 183 40.1 159.2 58.2 158 168.1
#> 18.02 3.53 10.55 12.43 12.89 16.67 21.49 9.24 18.00 10.55 19.34 20.14 23.72
#> 81 108 158.1 166 108.1 93 157 154.1 188.2 15.1 66 192.1 51
#> 14.06 18.29 20.14 19.98 18.29 10.33 15.10 12.63 16.16 22.68 22.13 16.44 18.23
#> 96 181.1 175 91 150.1 164 91.1 166.1 183.1 145.1 23 164.1 183.2
#> 14.54 16.46 21.91 5.33 20.33 23.60 5.33 19.98 9.24 10.07 16.92 23.60 9.24
#> 42.1 99.1 10.1 96.1 30 96.2 92.1 190.1 76.1 63 99.2 167 43
#> 12.43 21.19 10.53 14.54 17.43 14.54 22.92 20.81 19.22 22.77 21.19 15.55 12.10
#> 123 91.2 105 128.1 5.1 181.2 187 184 192.2 10.2 15.2 111 121
#> 13.00 5.33 19.75 20.35 16.43 16.46 9.92 17.77 16.44 10.53 22.68 17.45 24.00
#> 119 193 172 120 95 19 27 87 21 163 19.1 83 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 185 112 1 148 172.1 178 47 182 138 178.1 53 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 126 48 7 191 132 87.1 11 7.1 118 95.1 162 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 152.1 198 112.1 152.2 102 148.1 9 102.1 160 21.1 9.1 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 27.1 98 12 146 48.1 142 17 122.1 74 12.1 95.2 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 200 53.2 103.1 71 137 143.1 161 196.1 102.2 64 34 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 2 131 147.1 87.2 121.1 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[91]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01345108 0.42959409 0.31223798
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.146307292 -0.002597576 -0.240562560
#> grade_iii, Cure model
#> 0.722126717
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 195 11.76 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 108 18.29 1 39 0 1
#> 97 19.14 1 65 0 1
#> 105 19.75 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 177 12.53 1 75 0 0
#> 43 12.10 1 61 0 1
#> 195.1 11.76 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 78 23.88 1 43 0 0
#> 153.1 21.33 1 55 1 0
#> 40 18.00 1 28 1 0
#> 184 17.77 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 40.1 18.00 1 28 1 0
#> 45 17.42 1 54 0 1
#> 45.1 17.42 1 54 0 1
#> 101 9.97 1 10 0 1
#> 91 5.33 1 61 0 1
#> 157 15.10 1 47 0 0
#> 66 22.13 1 53 0 0
#> 170 19.54 1 43 0 1
#> 68 20.62 1 44 0 0
#> 6 15.64 1 39 0 0
#> 14.1 12.89 1 21 0 0
#> 157.1 15.10 1 47 0 0
#> 190 20.81 1 42 1 0
#> 189.1 10.51 1 NA 1 0
#> 78.1 23.88 1 43 0 0
#> 57 14.46 1 45 0 1
#> 42 12.43 1 49 0 1
#> 124 9.73 1 NA 1 0
#> 179.1 18.63 1 42 0 0
#> 183 9.24 1 67 1 0
#> 154 12.63 1 20 1 0
#> 170.1 19.54 1 43 0 1
#> 180 14.82 1 37 0 0
#> 25 6.32 1 34 1 0
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 188 16.16 1 46 0 1
#> 164 23.60 1 76 0 1
#> 77 7.27 1 67 0 1
#> 70 7.38 1 30 1 0
#> 111 17.45 1 47 0 1
#> 25.1 6.32 1 34 1 0
#> 123 13.00 1 44 1 0
#> 42.1 12.43 1 49 0 1
#> 78.2 23.88 1 43 0 0
#> 32 20.90 1 37 1 0
#> 157.2 15.10 1 47 0 0
#> 108.1 18.29 1 39 0 1
#> 88 18.37 1 47 0 0
#> 155 13.08 1 26 0 0
#> 171 16.57 1 41 0 1
#> 69 23.23 1 25 0 1
#> 145 10.07 1 65 1 0
#> 105.2 19.75 1 60 0 0
#> 37 12.52 1 57 1 0
#> 66.1 22.13 1 53 0 0
#> 133 14.65 1 57 0 0
#> 70.1 7.38 1 30 1 0
#> 129.1 23.41 1 53 1 0
#> 188.1 16.16 1 46 0 1
#> 14.2 12.89 1 21 0 0
#> 29 15.45 1 68 1 0
#> 16.1 8.71 1 71 0 1
#> 92 22.92 1 47 0 1
#> 39 15.59 1 37 0 1
#> 197 21.60 1 69 1 0
#> 153.2 21.33 1 55 1 0
#> 171.1 16.57 1 41 0 1
#> 133.1 14.65 1 57 0 0
#> 26 15.77 1 49 0 1
#> 157.3 15.10 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 164.1 23.60 1 76 0 1
#> 15 22.68 1 48 0 0
#> 45.2 17.42 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 81 14.06 1 34 0 0
#> 159 10.55 1 50 0 1
#> 187 9.92 1 39 1 0
#> 195.2 11.76 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 166 19.98 1 48 0 0
#> 179.2 18.63 1 42 0 0
#> 36 21.19 1 48 0 1
#> 30 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 68.1 20.62 1 44 0 0
#> 69.1 23.23 1 25 0 1
#> 140 12.68 1 59 1 0
#> 5 16.43 1 51 0 1
#> 99 21.19 1 38 0 1
#> 14.3 12.89 1 21 0 0
#> 90 20.94 1 50 0 1
#> 101.1 9.97 1 10 0 1
#> 175 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 189.2 10.51 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 187.1 9.92 1 39 1 0
#> 13 14.34 1 54 0 1
#> 43.1 12.10 1 61 0 1
#> 120 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 112 24.00 0 61 0 0
#> 122 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 152 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 1 24.00 0 23 1 0
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 115 24.00 0 NA 1 0
#> 47.1 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 132 24.00 0 55 0 0
#> 163 24.00 0 66 0 0
#> 82.1 24.00 0 34 0 0
#> 126 24.00 0 48 0 0
#> 120.1 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 120.2 24.00 0 68 0 1
#> 185.1 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 11 24.00 0 42 0 1
#> 148 24.00 0 61 1 0
#> 191 24.00 0 60 0 1
#> 103.1 24.00 0 56 1 0
#> 94.1 24.00 0 51 0 1
#> 122.1 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 122.2 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 135 24.00 0 58 1 0
#> 82.2 24.00 0 34 0 0
#> 131 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 54 24.00 0 53 1 0
#> 104 24.00 0 50 1 0
#> 82.3 24.00 0 34 0 0
#> 75 24.00 0 21 1 0
#> 33 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 115.1 24.00 0 NA 1 0
#> 198 24.00 0 66 0 1
#> 83 24.00 0 6 0 0
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 83.1 24.00 0 6 0 0
#> 143 24.00 0 51 0 0
#> 17.1 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 112.2 24.00 0 61 0 0
#> 115.2 24.00 0 NA 1 0
#> 198.1 24.00 0 66 0 1
#> 53 24.00 0 32 0 1
#> 103.2 24.00 0 56 1 0
#> 163.1 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 17.2 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 38.1 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 75.1 24.00 0 21 1 0
#> 103.3 24.00 0 56 1 0
#> 186 24.00 0 45 1 0
#> 198.2 24.00 0 66 0 1
#> 67.1 24.00 0 25 0 0
#> 126.1 24.00 0 48 0 0
#> 83.2 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 118 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 138.1 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 21.1 24.00 0 47 0 0
#> 118.1 24.00 0 44 1 0
#> 9.1 24.00 0 31 1 0
#> 71.2 24.00 0 51 0 0
#> 185.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.146 NA NA NA
#> 2 age, Cure model -0.00260 NA NA NA
#> 3 grade_ii, Cure model -0.241 NA NA NA
#> 4 grade_iii, Cure model 0.722 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0135 NA NA NA
#> 2 grade_ii, Survival model 0.430 NA NA NA
#> 3 grade_iii, Survival model 0.312 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.146307 -0.002598 -0.240563 0.722127
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 250.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.146307292 -0.002597576 -0.240562560 0.722126717
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01345108 0.42959409 0.31223798
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.5653617723 0.3024332642 0.2534965992 0.2068390059 0.1560883459
#> [6] 0.1560883459 0.7162168346 0.7686943092 0.0778198621 0.8897188997
#> [11] 0.2159755127 0.0009628672 0.0778198621 0.2729952589 0.2924190797
#> [16] 0.6402691178 0.2729952589 0.3426110349 0.3426110349 0.8224505735
#> [21] 0.9860237054 0.4832399926 0.0478178743 0.1806964351 0.1330675214
#> [26] 0.4493523005 0.6402691178 0.4832399926 0.1256862202 0.0009628672
#> [31] 0.5776525213 0.7424029021 0.2159755127 0.8761029098 0.7033070003
#> [36] 0.1806964351 0.5291385314 0.9584239980 0.0162164854 0.0057278325
#> [41] 0.4164444558 0.0088328972 0.9445343906 0.9171374271 0.3221777995
#> [46] 0.9584239980 0.6276140297 0.7424029021 0.0009628672 0.1183594964
#> [51] 0.4832399926 0.2534965992 0.2436996356 0.6149970526 0.3842445553
#> [56] 0.0246019321 0.8088590564 0.1560883459 0.7292762314 0.0478178743
#> [61] 0.5411118023 0.9171374271 0.0162164854 0.4164444558 0.6402691178
#> [66] 0.4718588798 0.8897188997 0.0330849160 0.4605823141 0.0651779645
#> [71] 0.0778198621 0.3842445553 0.5411118023 0.4382357029 0.4832399926
#> [76] 0.0088328972 0.0378192350 0.3426110349 0.0651779645 0.6024560120
#> [81] 0.7953490406 0.8492383117 0.3024332642 0.1481482218 0.2159755127
#> [86] 0.0972144744 0.3322923695 0.1978728303 0.1330675214 0.0246019321
#> [91] 0.6903557651 0.4055550114 0.0972144744 0.6402691178 0.1110626415
#> [96] 0.8224505735 0.0590147514 0.0378192350 0.3735653185 0.8492383117
#> [101] 0.5900100687 0.7686943092 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 96 117 108 97 105 105.1 177 43 153 16 179 78 153.1
#> 14.54 17.46 18.29 19.14 19.75 19.75 12.53 12.10 21.33 8.71 18.63 23.88 21.33
#> 40 184 14 40.1 45 45.1 101 91 157 66 170 68 6
#> 18.00 17.77 12.89 18.00 17.42 17.42 9.97 5.33 15.10 22.13 19.54 20.62 15.64
#> 14.1 157.1 190 78.1 57 42 179.1 183 154 170.1 180 25 129
#> 12.89 15.10 20.81 23.88 14.46 12.43 18.63 9.24 12.63 19.54 14.82 6.32 23.41
#> 86 188 164 77 70 111 25.1 123 42.1 78.2 32 157.2 108.1
#> 23.81 16.16 23.60 7.27 7.38 17.45 6.32 13.00 12.43 23.88 20.90 15.10 18.29
#> 88 155 171 69 145 105.2 37 66.1 133 70.1 129.1 188.1 14.2
#> 18.37 13.08 16.57 23.23 10.07 19.75 12.52 22.13 14.65 7.38 23.41 16.16 12.89
#> 29 16.1 92 39 197 153.2 171.1 133.1 26 157.3 164.1 15 45.2
#> 15.45 8.71 22.92 15.59 21.60 21.33 16.57 14.65 15.77 15.10 23.60 22.68 17.42
#> 197.1 81 159 187 117.1 166 179.2 36 30 55 68.1 69.1 140
#> 21.60 14.06 10.55 9.92 17.46 19.98 18.63 21.19 17.43 19.34 20.62 23.23 12.68
#> 5 99 14.3 90 101.1 175 15.1 106 187.1 13 43.1 120 160
#> 16.43 21.19 12.89 20.94 9.97 21.91 22.68 16.67 9.92 14.34 12.10 24.00 24.00
#> 103 38 94 112 122 47 152 141 161 1 17 82 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 21 132 163 82.1 126 120.1 74 120.2 185.1 112.1 11 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 103.1 94.1 122.1 74.1 122.2 196 135 82.2 131 9 71 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 104 82.3 75 33 102 198 83 34 146 83.1 143 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 112.2 198.1 53 103.2 163.1 71.1 67 17.2 28 38.1 132.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.3 186 198.2 67.1 126.1 83.2 138 147 118 65 121 138.1 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 118.1 9.1 71.2 185.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[92]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002457353 0.880731603 0.454440204
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.063925875 0.001460444 -0.320837352
#> grade_iii, Cure model
#> 0.898584068
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 68 20.62 1 44 0 0
#> 45 17.42 1 54 0 1
#> 91 5.33 1 61 0 1
#> 136 21.83 1 43 0 1
#> 30 17.43 1 78 0 0
#> 79 16.23 1 54 1 0
#> 50 10.02 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 110 17.56 1 65 0 1
#> 105 19.75 1 60 0 0
#> 157 15.10 1 47 0 0
#> 108 18.29 1 39 0 1
#> 39 15.59 1 37 0 1
#> 127 3.53 1 62 0 1
#> 100 16.07 1 60 0 0
#> 194 22.40 1 38 0 1
#> 136.1 21.83 1 43 0 1
#> 91.1 5.33 1 61 0 1
#> 127.1 3.53 1 62 0 1
#> 194.1 22.40 1 38 0 1
#> 69 23.23 1 25 0 1
#> 32 20.90 1 37 1 0
#> 150 20.33 1 48 0 0
#> 78 23.88 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 136.2 21.83 1 43 0 1
#> 154 12.63 1 20 1 0
#> 194.2 22.40 1 38 0 1
#> 175 21.91 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 5 16.43 1 51 0 1
#> 42 12.43 1 49 0 1
#> 166 19.98 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 14 12.89 1 21 0 0
#> 89 11.44 1 NA 0 0
#> 192 16.44 1 31 1 0
#> 125 15.65 1 67 1 0
#> 43 12.10 1 61 0 1
#> 66 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 25 6.32 1 34 1 0
#> 63 22.77 1 31 1 0
#> 43.1 12.10 1 61 0 1
#> 171 16.57 1 41 0 1
#> 106 16.67 1 49 1 0
#> 107 11.18 1 54 1 0
#> 153 21.33 1 55 1 0
#> 190 20.81 1 42 1 0
#> 8 18.43 1 32 0 0
#> 189 10.51 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 39.1 15.59 1 37 0 1
#> 40 18.00 1 28 1 0
#> 179 18.63 1 42 0 0
#> 125.1 15.65 1 67 1 0
#> 52 10.42 1 52 0 1
#> 113 22.86 1 34 0 0
#> 183 9.24 1 67 1 0
#> 190.1 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 101 9.97 1 10 0 1
#> 157.1 15.10 1 47 0 0
#> 190.2 20.81 1 42 1 0
#> 194.3 22.40 1 38 0 1
#> 164 23.60 1 76 0 1
#> 89.1 11.44 1 NA 0 0
#> 8.1 18.43 1 32 0 0
#> 14.1 12.89 1 21 0 0
#> 37.1 12.52 1 57 1 0
#> 175.1 21.91 1 43 0 0
#> 55 19.34 1 69 0 1
#> 30.1 17.43 1 78 0 0
#> 101.1 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 171.1 16.57 1 41 0 1
#> 68.1 20.62 1 44 0 0
#> 187 9.92 1 39 1 0
#> 60 13.15 1 38 1 0
#> 159.1 10.55 1 50 0 1
#> 91.2 5.33 1 61 0 1
#> 60.1 13.15 1 38 1 0
#> 89.2 11.44 1 NA 0 0
#> 194.4 22.40 1 38 0 1
#> 164.1 23.60 1 76 0 1
#> 168.1 23.72 1 70 0 0
#> 164.2 23.60 1 76 0 1
#> 188 16.16 1 46 0 1
#> 10 10.53 1 34 0 0
#> 155 13.08 1 26 0 0
#> 51 18.23 1 83 0 1
#> 24 23.89 1 38 0 0
#> 88 18.37 1 47 0 0
#> 117.1 17.46 1 26 0 1
#> 69.1 23.23 1 25 0 1
#> 179.1 18.63 1 42 0 0
#> 39.2 15.59 1 37 0 1
#> 24.1 23.89 1 38 0 0
#> 88.1 18.37 1 47 0 0
#> 175.2 21.91 1 43 0 0
#> 89.3 11.44 1 NA 0 0
#> 10.1 10.53 1 34 0 0
#> 42.1 12.43 1 49 0 1
#> 169.1 22.41 1 46 0 0
#> 195.1 11.76 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 14.2 12.89 1 21 0 0
#> 8.2 18.43 1 32 0 0
#> 25.1 6.32 1 34 1 0
#> 119 24.00 0 17 0 0
#> 83 24.00 0 6 0 0
#> 11 24.00 0 42 0 1
#> 20 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 142 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 80 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 11.1 24.00 0 42 0 1
#> 34 24.00 0 36 0 0
#> 22 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 135 24.00 0 58 1 0
#> 38 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 122 24.00 0 66 0 0
#> 38.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 74 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 198 24.00 0 66 0 1
#> 172.2 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 31 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 178 24.00 0 52 1 0
#> 21.1 24.00 0 47 0 0
#> 160.1 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 174.1 24.00 0 49 1 0
#> 2 24.00 0 9 0 0
#> 182 24.00 0 35 0 0
#> 67 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 174.2 24.00 0 49 1 0
#> 146 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 3 24.00 0 31 1 0
#> 160.2 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 185 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 73.1 24.00 0 NA 0 1
#> 48.2 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 185.1 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 122.1 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 20.1 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 74.1 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 162.1 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 17 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 71.1 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 146.1 24.00 0 63 1 0
#> 2.1 24.00 0 9 0 0
#> 132.1 24.00 0 55 0 0
#> 182.1 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 94.1 24.00 0 51 0 1
#> 87 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 73.2 24.00 0 NA 0 1
#> 120 24.00 0 68 0 1
#> 142.1 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 143.1 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0639 NA NA NA
#> 2 age, Cure model 0.00146 NA NA NA
#> 3 grade_ii, Cure model -0.321 NA NA NA
#> 4 grade_iii, Cure model 0.899 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00246 NA NA NA
#> 2 grade_ii, Survival model 0.881 NA NA NA
#> 3 grade_iii, Survival model 0.454 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.06393 0.00146 -0.32084 0.89858
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 245.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.063925875 0.001460444 -0.320837352 0.898584068
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002457353 0.880731603 0.454440204
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.41216197 0.61357109 0.96503330 0.32896018 0.59501167 0.67646833
#> [7] 0.81586473 0.56710245 0.45090594 0.75186372 0.53812498 0.71910898
#> [13] 0.98602536 0.69374702 0.22813587 0.32896018 0.96503330 0.98602536
#> [19] 0.22813587 0.14524428 0.37314910 0.43138793 0.04455205 0.20168734
#> [25] 0.32896018 0.82378818 0.22813587 0.29434480 0.66768162 0.84687830
#> [31] 0.44113492 0.57655271 0.79207577 0.65884962 0.70237891 0.86203426
#> [37] 0.28246952 0.83161402 0.95087735 0.18819683 0.86203426 0.64101050
#> [43] 0.63191992 0.87709595 0.36212362 0.38379619 0.48977826 0.88458751
#> [49] 0.71910898 0.55759790 0.47043800 0.70237891 0.91424994 0.17339645
#> [55] 0.94364099 0.38379619 0.61357109 0.92167743 0.75186372 0.38379619
#> [61] 0.22813587 0.10130201 0.48977826 0.79207577 0.83161402 0.29434480
#> [67] 0.46070608 0.59501167 0.92167743 0.06433561 0.64101050 0.41216197
#> [73] 0.93634610 0.76817284 0.88458751 0.96503330 0.76817284 0.22813587
#> [79] 0.10130201 0.06433561 0.10130201 0.68512984 0.89940892 0.78407760
#> [85] 0.54788606 0.01486159 0.51862875 0.57655271 0.14524428 0.47043800
#> [91] 0.71910898 0.01486159 0.51862875 0.29434480 0.89940892 0.84687830
#> [97] 0.20168734 0.74368392 0.79207577 0.48977826 0.95087735 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 68 45 91 136 30 79 140 110 105 157 108 39 127
#> 20.62 17.42 5.33 21.83 17.43 16.23 12.68 17.56 19.75 15.10 18.29 15.59 3.53
#> 100 194 136.1 91.1 127.1 194.1 69 32 150 78 169 136.2 154
#> 16.07 22.40 21.83 5.33 3.53 22.40 23.23 20.90 20.33 23.88 22.41 21.83 12.63
#> 194.2 175 5 42 166 117 14 192 125 43 66 37 25
#> 22.40 21.91 16.43 12.43 19.98 17.46 12.89 16.44 15.65 12.10 22.13 12.52 6.32
#> 63 43.1 171 106 107 153 190 8 159 39.1 40 179 125.1
#> 22.77 12.10 16.57 16.67 11.18 21.33 20.81 18.43 10.55 15.59 18.00 18.63 15.65
#> 52 113 183 190.1 45.1 101 157.1 190.2 194.3 164 8.1 14.1 37.1
#> 10.42 22.86 9.24 20.81 17.42 9.97 15.10 20.81 22.40 23.60 18.43 12.89 12.52
#> 175.1 55 30.1 101.1 168 171.1 68.1 187 60 159.1 91.2 60.1 194.4
#> 21.91 19.34 17.43 9.97 23.72 16.57 20.62 9.92 13.15 10.55 5.33 13.15 22.40
#> 164.1 168.1 164.2 188 10 155 51 24 88 117.1 69.1 179.1 39.2
#> 23.60 23.72 23.60 16.16 10.53 13.08 18.23 23.89 18.37 17.46 23.23 18.63 15.59
#> 24.1 88.1 175.2 10.1 42.1 169.1 18 14.2 8.2 25.1 119 83 11
#> 23.89 18.37 21.91 10.53 12.43 22.41 15.21 12.89 18.43 6.32 24.00 24.00 24.00
#> 20 174 71 48 132 142 137 80 121 191 65 11.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 172 1 135 38 152 122 38.1 172.1 74 198 172.2 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 21 160 48.1 121.1 103 178 21.1 160.1 135.1 174.1 2 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 162 174.2 146 19 3 160.2 116 185 119.1 48.2 191.1 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 27 122.1 143 20.1 102 82 74.1 84 162.1 94 17 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 35 62 148 146.1 2.1 132.1 182.1 46 94.1 87 118 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 12 143.1 3.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[93]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003000843 0.123475052 -0.149260106
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.283042959 0.008869369 -0.548206571
#> grade_iii, Cure model
#> 0.592627415
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 45 17.42 1 54 0 1
#> 16 8.71 1 71 0 1
#> 180 14.82 1 37 0 0
#> 99 21.19 1 38 0 1
#> 166 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 25 6.32 1 34 1 0
#> 188 16.16 1 46 0 1
#> 41 18.02 1 40 1 0
#> 159 10.55 1 50 0 1
#> 81 14.06 1 34 0 0
#> 86 23.81 1 58 0 1
#> 130 16.47 1 53 0 1
#> 14 12.89 1 21 0 0
#> 66 22.13 1 53 0 0
#> 170 19.54 1 43 0 1
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 187 9.92 1 39 1 0
#> 113 22.86 1 34 0 0
#> 90 20.94 1 50 0 1
#> 92 22.92 1 47 0 1
#> 125 15.65 1 67 1 0
#> 90.1 20.94 1 50 0 1
#> 177 12.53 1 75 0 0
#> 113.1 22.86 1 34 0 0
#> 108 18.29 1 39 0 1
#> 16.1 8.71 1 71 0 1
#> 192 16.44 1 31 1 0
#> 43 12.10 1 61 0 1
#> 150 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 179 18.63 1 42 0 0
#> 97 19.14 1 65 0 1
#> 167 15.55 1 56 1 0
#> 97.1 19.14 1 65 0 1
#> 133 14.65 1 57 0 0
#> 117 17.46 1 26 0 1
#> 26 15.77 1 49 0 1
#> 128 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 108.1 18.29 1 39 0 1
#> 93 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 30 17.43 1 78 0 0
#> 26.1 15.77 1 49 0 1
#> 183 9.24 1 67 1 0
#> 68.1 20.62 1 44 0 0
#> 26.2 15.77 1 49 0 1
#> 190 20.81 1 42 1 0
#> 85 16.44 1 36 0 0
#> 55 19.34 1 69 0 1
#> 184 17.77 1 38 0 0
#> 45.1 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 159.1 10.55 1 50 0 1
#> 128.1 20.35 1 35 0 1
#> 188.1 16.16 1 46 0 1
#> 177.1 12.53 1 75 0 0
#> 136 21.83 1 43 0 1
#> 117.1 17.46 1 26 0 1
#> 114.1 13.68 1 NA 0 0
#> 79.1 16.23 1 54 1 0
#> 166.1 19.98 1 48 0 0
#> 197 21.60 1 69 1 0
#> 177.2 12.53 1 75 0 0
#> 181 16.46 1 45 0 1
#> 155 13.08 1 26 0 0
#> 180.1 14.82 1 37 0 0
#> 51 18.23 1 83 0 1
#> 10 10.53 1 34 0 0
#> 125.1 15.65 1 67 1 0
#> 130.1 16.47 1 53 0 1
#> 183.1 9.24 1 67 1 0
#> 23 16.92 1 61 0 0
#> 130.2 16.47 1 53 0 1
#> 41.1 18.02 1 40 1 0
#> 166.2 19.98 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 113.2 22.86 1 34 0 0
#> 23.1 16.92 1 61 0 0
#> 89 11.44 1 NA 0 0
#> 179.1 18.63 1 42 0 0
#> 199.1 19.81 1 NA 0 1
#> 61 10.12 1 36 0 1
#> 55.1 19.34 1 69 0 1
#> 129 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 45.2 17.42 1 54 0 1
#> 85.1 16.44 1 36 0 0
#> 50 10.02 1 NA 1 0
#> 155.1 13.08 1 26 0 0
#> 23.2 16.92 1 61 0 0
#> 192.1 16.44 1 31 1 0
#> 86.1 23.81 1 58 0 1
#> 50.1 10.02 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 4 17.64 1 NA 0 1
#> 194 22.40 1 38 0 1
#> 183.2 9.24 1 67 1 0
#> 23.3 16.92 1 61 0 0
#> 128.2 20.35 1 35 0 1
#> 197.1 21.60 1 69 1 0
#> 70 7.38 1 30 1 0
#> 166.3 19.98 1 48 0 0
#> 164 23.60 1 76 0 1
#> 117.2 17.46 1 26 0 1
#> 30.1 17.43 1 78 0 0
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 72 24.00 0 40 0 1
#> 176 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 65 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 147 24.00 0 76 1 0
#> 94 24.00 0 51 0 1
#> 20 24.00 0 46 1 0
#> 46 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 38 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 120 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 21 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 22 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 142 24.00 0 53 0 0
#> 193 24.00 0 45 0 1
#> 46.1 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 64 24.00 0 43 0 0
#> 9 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 20.2 24.00 0 46 1 0
#> 98 24.00 0 34 1 0
#> 75.1 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 62 24.00 0 71 0 0
#> 53.1 24.00 0 32 0 1
#> 11 24.00 0 42 0 1
#> 119 24.00 0 17 0 0
#> 34 24.00 0 36 0 0
#> 3.1 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 147.1 24.00 0 76 1 0
#> 142.1 24.00 0 53 0 0
#> 38.1 24.00 0 31 1 0
#> 46.2 24.00 0 71 0 0
#> 102 24.00 0 49 0 0
#> 132.1 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 3.2 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 22.1 24.00 0 52 1 0
#> 121.1 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 27 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 182 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 112.1 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 185 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 162 24.00 0 51 0 0
#> 147.2 24.00 0 76 1 0
#> 151 24.00 0 42 0 0
#> 152 24.00 0 36 0 1
#> 132.2 24.00 0 55 0 0
#> 198.1 24.00 0 66 0 1
#> 17 24.00 0 38 0 1
#> 20.3 24.00 0 46 1 0
#> 46.3 24.00 0 71 0 0
#> 46.4 24.00 0 71 0 0
#> 162.1 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#> 22.2 24.00 0 52 1 0
#> 74.1 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 73.1 24.00 0 NA 0 1
#> 48 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.283 NA NA NA
#> 2 age, Cure model 0.00887 NA NA NA
#> 3 grade_ii, Cure model -0.548 NA NA NA
#> 4 grade_iii, Cure model 0.593 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00300 NA NA NA
#> 2 grade_ii, Survival model 0.123 NA NA NA
#> 3 grade_iii, Survival model -0.149 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.283043 0.008869 -0.548207 0.592627
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 251.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.283042959 0.008869369 -0.548206571 0.592627415
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003000843 0.123475052 -0.149260106
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.399231338 0.942983266 0.677693198 0.104366011 0.186853582 0.710150151
#> [7] 0.977123747 0.571290754 0.322066595 0.830785033 0.721088052 0.002818743
#> [13] 0.468611215 0.753834830 0.058189411 0.220248644 0.656035696 0.136891317
#> [19] 0.898038359 0.032121244 0.112428897 0.024767363 0.634644702 0.112428897
#> [25] 0.775796627 0.032121244 0.293522310 0.942983266 0.509722075 0.819639397
#> [31] 0.178108531 0.550486671 0.265555491 0.247186292 0.666860613 0.247186292
#> [37] 0.699257135 0.350824817 0.602909376 0.153295907 0.592285820 0.293522310
#> [43] 0.875432668 0.764820891 0.379592291 0.602909376 0.909356628 0.136891317
#> [49] 0.602909376 0.128556051 0.509722075 0.229206723 0.341127662 0.399231338
#> [55] 0.988543021 0.830785033 0.153295907 0.571290754 0.775796627 0.065759293
#> [61] 0.350824817 0.550486671 0.186853582 0.073547749 0.775796627 0.499241559
#> [67] 0.732042072 0.677693198 0.312388880 0.853080504 0.634644702 0.468611215
#> [73] 0.909356628 0.428903759 0.468611215 0.322066595 0.186853582 0.853080504
#> [79] 0.032121244 0.428903759 0.265555491 0.886719171 0.229206723 0.017935175
#> [85] 0.088550758 0.399231338 0.509722075 0.732042072 0.428903759 0.509722075
#> [91] 0.002818743 0.808536451 0.050762738 0.909356628 0.428903759 0.153295907
#> [97] 0.073547749 0.965701581 0.186853582 0.011223203 0.350824817 0.379592291
#> [103] 0.284076857 0.096445010 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 45 16 180 99 166 13 25 188 41 159 81 86 130
#> 17.42 8.71 14.82 21.19 19.98 14.34 6.32 16.16 18.02 10.55 14.06 23.81 16.47
#> 14 66 170 39 68 187 113 90 92 125 90.1 177 113.1
#> 12.89 22.13 19.54 15.59 20.62 9.92 22.86 20.94 22.92 15.65 20.94 12.53 22.86
#> 108 16.1 192 43 150 79 179 97 167 97.1 133 117 26
#> 18.29 8.71 16.44 12.10 20.33 16.23 18.63 19.14 15.55 19.14 14.65 17.46 15.77
#> 128 100 108.1 93 154 30 26.1 183 68.1 26.2 190 85 55
#> 20.35 16.07 18.29 10.33 12.63 17.43 15.77 9.24 20.62 15.77 20.81 16.44 19.34
#> 184 45.1 127 159.1 128.1 188.1 177.1 136 117.1 79.1 166.1 197 177.2
#> 17.77 17.42 3.53 10.55 20.35 16.16 12.53 21.83 17.46 16.23 19.98 21.60 12.53
#> 181 155 180.1 51 10 125.1 130.1 183.1 23 130.2 41.1 166.2 10.1
#> 16.46 13.08 14.82 18.23 10.53 15.65 16.47 9.24 16.92 16.47 18.02 19.98 10.53
#> 113.2 23.1 179.1 61 55.1 129 139 45.2 85.1 155.1 23.2 192.1 86.1
#> 22.86 16.92 18.63 10.12 19.34 23.41 21.49 17.42 16.44 13.08 16.92 16.44 23.81
#> 42 194 183.2 23.3 128.2 197.1 70 166.3 164 117.2 30.1 8 153
#> 12.43 22.40 9.24 16.92 20.35 21.60 7.38 19.98 23.60 17.46 17.43 18.43 21.33
#> 72 176 121 65 12 147 94 20 46 146 135 38 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 138 132 21 22 53 142 193 46.1 3 21.1 112 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 20.1 75 19 20.2 98 75.1 1 62 53.1 11 119 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 137 109 74 147.1 142.1 38.1 46.2 102 132.1 141 31 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 84 22.1 121.1 144 33 27 54 182 47 143 143.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 116 185 198 162 147.2 151 152 132.2 198.1 17 20.3 46.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.4 162.1 137.1 22.2 74.1 87 48 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[94]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0008711646 0.7792966226 0.6231789637
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.83383895 0.01265619 0.15506766
#> grade_iii, Cure model
#> 1.02057739
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 128 20.35 1 35 0 1
#> 76 19.22 1 54 0 1
#> 101 9.97 1 10 0 1
#> 56 12.21 1 60 0 0
#> 194 22.40 1 38 0 1
#> 42 12.43 1 49 0 1
#> 111 17.45 1 47 0 1
#> 29 15.45 1 68 1 0
#> 15 22.68 1 48 0 0
#> 91 5.33 1 61 0 1
#> 30 17.43 1 78 0 0
#> 124 9.73 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 13 14.34 1 54 0 1
#> 96 14.54 1 33 0 1
#> 51 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 39 15.59 1 37 0 1
#> 140 12.68 1 59 1 0
#> 189 10.51 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 123 13.00 1 44 1 0
#> 23 16.92 1 61 0 0
#> 41.1 18.02 1 40 1 0
#> 99 21.19 1 38 0 1
#> 37 12.52 1 57 1 0
#> 18 15.21 1 49 1 0
#> 164 23.60 1 76 0 1
#> 189.1 10.51 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 117 17.46 1 26 0 1
#> 26 15.77 1 49 0 1
#> 58 19.34 1 39 0 0
#> 171.1 16.57 1 41 0 1
#> 187 9.92 1 39 1 0
#> 55 19.34 1 69 0 1
#> 184 17.77 1 38 0 0
#> 39.1 15.59 1 37 0 1
#> 96.1 14.54 1 33 0 1
#> 42.1 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 60 13.15 1 38 1 0
#> 184.1 17.77 1 38 0 0
#> 99.1 21.19 1 38 0 1
#> 68 20.62 1 44 0 0
#> 26.1 15.77 1 49 0 1
#> 197 21.60 1 69 1 0
#> 91.1 5.33 1 61 0 1
#> 59.1 10.16 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 81 14.06 1 34 0 0
#> 129 23.41 1 53 1 0
#> 113 22.86 1 34 0 0
#> 18.1 15.21 1 49 1 0
#> 41.2 18.02 1 40 1 0
#> 66.1 22.13 1 53 0 0
#> 114 13.68 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 134.1 17.81 1 47 1 0
#> 107.1 11.18 1 54 1 0
#> 51.2 18.23 1 83 0 1
#> 88.1 18.37 1 47 0 0
#> 179 18.63 1 42 0 0
#> 69 23.23 1 25 0 1
#> 52 10.42 1 52 0 1
#> 170 19.54 1 43 0 1
#> 93 10.33 1 52 0 1
#> 127 3.53 1 62 0 1
#> 168 23.72 1 70 0 0
#> 41.3 18.02 1 40 1 0
#> 117.1 17.46 1 26 0 1
#> 16 8.71 1 71 0 1
#> 184.2 17.77 1 38 0 0
#> 45 17.42 1 54 0 1
#> 76.1 19.22 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 88.2 18.37 1 47 0 0
#> 52.1 10.42 1 52 0 1
#> 52.2 10.42 1 52 0 1
#> 76.2 19.22 1 54 0 1
#> 10 10.53 1 34 0 0
#> 26.2 15.77 1 49 0 1
#> 40.1 18.00 1 28 1 0
#> 89 11.44 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 13.1 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 91.2 5.33 1 61 0 1
#> 14 12.89 1 21 0 0
#> 16.1 8.71 1 71 0 1
#> 158 20.14 1 74 1 0
#> 69.1 23.23 1 25 0 1
#> 24 23.89 1 38 0 0
#> 93.1 10.33 1 52 0 1
#> 110 17.56 1 65 0 1
#> 40.2 18.00 1 28 1 0
#> 114.1 13.68 1 NA 0 0
#> 128.1 20.35 1 35 0 1
#> 79 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 139 21.49 1 63 1 0
#> 149 8.37 1 33 1 0
#> 60.1 13.15 1 38 1 0
#> 149.1 8.37 1 33 1 0
#> 41.4 18.02 1 40 1 0
#> 169 22.41 1 46 0 0
#> 5 16.43 1 51 0 1
#> 167 15.55 1 56 1 0
#> 59.2 10.16 1 NA 1 0
#> 67 24.00 0 25 0 0
#> 186 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 165.1 24.00 0 47 0 0
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 65 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 156 24.00 0 50 1 0
#> 151 24.00 0 42 0 0
#> 27 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 141 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 82 24.00 0 34 0 0
#> 20.1 24.00 0 46 1 0
#> 35 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 196 24.00 0 19 0 0
#> 191.1 24.00 0 60 0 1
#> 186.1 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 174 24.00 0 49 1 0
#> 147 24.00 0 76 1 0
#> 27.1 24.00 0 63 1 0
#> 160.1 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 98 24.00 0 34 1 0
#> 135 24.00 0 58 1 0
#> 146 24.00 0 63 1 0
#> 53.1 24.00 0 32 0 1
#> 54.1 24.00 0 53 1 0
#> 118 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 174.1 24.00 0 49 1 0
#> 31 24.00 0 36 0 1
#> 173.2 24.00 0 19 0 1
#> 67.1 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 64 24.00 0 43 0 0
#> 28 24.00 0 67 1 0
#> 174.2 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 65.2 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 67.2 24.00 0 25 0 0
#> 176.1 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 83 24.00 0 6 0 0
#> 17 24.00 0 38 0 1
#> 20.2 24.00 0 46 1 0
#> 142.1 24.00 0 53 0 0
#> 31.1 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 94.1 24.00 0 51 0 1
#> 17.1 24.00 0 38 0 1
#> 94.2 24.00 0 51 0 1
#> 198.1 24.00 0 66 0 1
#> 120 24.00 0 68 0 1
#> 83.1 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 1 24.00 0 23 1 0
#> 71.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 104 24.00 0 50 1 0
#> 161 24.00 0 45 0 0
#> 131 24.00 0 66 0 0
#> 21.1 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 83.2 24.00 0 6 0 0
#> 12 24.00 0 63 0 0
#> 64.1 24.00 0 43 0 0
#> 46.1 24.00 0 71 0 0
#> 17.2 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.834 NA NA NA
#> 2 age, Cure model 0.0127 NA NA NA
#> 3 grade_ii, Cure model 0.155 NA NA NA
#> 4 grade_iii, Cure model 1.02 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000871 NA NA NA
#> 2 grade_ii, Survival model 0.779 NA NA NA
#> 3 grade_iii, Survival model 0.623 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83384 0.01266 0.15507 1.02058
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 250.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83383895 0.01265619 0.15506766 1.02057739
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0008711646 0.7792966226 0.6231789637
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.28740065 0.54789369 0.38259516 0.45010820 0.94575081 0.88822613
#> [7] 0.25747738 0.87634302 0.67540610 0.78201598 0.22272944 0.97874160
#> [13] 0.68292545 0.70530721 0.81448075 0.80167635 0.51978345 0.61361899
#> [19] 0.76170128 0.85811216 0.49005901 0.84580393 0.69787526 0.54789369
#> [25] 0.34511338 0.87030343 0.78868116 0.12348611 0.86420925 0.66029339
#> [31] 0.73415543 0.42863714 0.70530721 0.95136170 0.42863714 0.62925393
#> [37] 0.76170128 0.80167635 0.87634302 0.90009483 0.83342614 0.62925393
#> [43] 0.34511338 0.36996842 0.73415543 0.31718035 0.97874160 0.51978345
#> [49] 0.82709582 0.15007974 0.20527256 0.78868116 0.54789369 0.28740065
#> [55] 0.58954198 0.61361899 0.90009483 0.51978345 0.49005901 0.47991744
#> [61] 0.17176320 0.91748968 0.41747648 0.93450369 0.99468465 0.08975823
#> [67] 0.54789369 0.66029339 0.95693136 0.62925393 0.69043898 0.45010820
#> [73] 0.25747738 0.49005901 0.91748968 0.91748968 0.45010820 0.91167979
#> [79] 0.73415543 0.58954198 0.75476883 0.81448075 0.05539306 0.97874160
#> [85] 0.85195846 0.95693136 0.40602941 0.17176320 0.02105244 0.93450369
#> [91] 0.65253113 0.58954198 0.38259516 0.72702783 0.89418555 0.33152978
#> [97] 0.96791287 0.83342614 0.96791287 0.54789369 0.24012882 0.71980929
#> [103] 0.77527536 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 66 41 128 76 101 56 194 42 111 29 15 91 30
#> 22.13 18.02 20.35 19.22 9.97 12.21 22.40 12.43 17.45 15.45 22.68 5.33 17.43
#> 171 13 96 51 134 39 140 88 123 23 41.1 99 37
#> 16.57 14.34 14.54 18.23 17.81 15.59 12.68 18.37 13.00 16.92 18.02 21.19 12.52
#> 18 164 177 117 26 58 171.1 187 55 184 39.1 96.1 42.1
#> 15.21 23.60 12.53 17.46 15.77 19.34 16.57 9.92 19.34 17.77 15.59 14.54 12.43
#> 107 60 184.1 99.1 68 26.1 197 91.1 51.1 81 129 113 18.1
#> 11.18 13.15 17.77 21.19 20.62 15.77 21.60 5.33 18.23 14.06 23.41 22.86 15.21
#> 41.2 66.1 40 134.1 107.1 51.2 88.1 179 69 52 170 93 127
#> 18.02 22.13 18.00 17.81 11.18 18.23 18.37 18.63 23.23 10.42 19.54 10.33 3.53
#> 168 41.3 117.1 16 184.2 45 76.1 194.1 88.2 52.1 52.2 76.2 10
#> 23.72 18.02 17.46 8.71 17.77 17.42 19.22 22.40 18.37 10.42 10.42 19.22 10.53
#> 26.2 40.1 6 13.1 78 91.2 14 16.1 158 69.1 24 93.1 110
#> 15.77 18.00 15.64 14.34 23.88 5.33 12.89 8.71 20.14 23.23 23.89 10.33 17.56
#> 40.2 128.1 79 49 139 149 60.1 149.1 41.4 169 5 167 67
#> 18.00 20.35 16.23 12.19 21.49 8.37 13.15 8.37 18.02 22.41 16.43 15.55 24.00
#> 186 165 142 87 165.1 33 182 65 198 21 72 156 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 71 160 191 141 65.1 20 82 20.1 35 54 196 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 176 193 174 147 27.1 160.1 182.1 173 53 98 135 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 54.1 118 173.1 174.1 31 173.2 67.1 148 64 28 174.2 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 94 65.2 119 67.2 176.1 46 151.1 83 17 20.2 142.1 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 94.1 17.1 94.2 198.1 120 83.1 103 1 71.1 62 104 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 21.1 83.2 12 64.1 46.1 17.2 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[95]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00085246 0.42859816 -0.12871448
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.026033429 -0.009777403 0.401580261
#> grade_iii, Cure model
#> 1.473006596
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 63 22.77 1 31 1 0
#> 49 12.19 1 48 1 0
#> 177 12.53 1 75 0 0
#> 8 18.43 1 32 0 0
#> 113 22.86 1 34 0 0
#> 18 15.21 1 49 1 0
#> 170 19.54 1 43 0 1
#> 114 13.68 1 NA 0 0
#> 171 16.57 1 41 0 1
#> 110 17.56 1 65 0 1
#> 164 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 179 18.63 1 42 0 0
#> 159 10.55 1 50 0 1
#> 41 18.02 1 40 1 0
#> 92 22.92 1 47 0 1
#> 175 21.91 1 43 0 0
#> 45 17.42 1 54 0 1
#> 42 12.43 1 49 0 1
#> 5 16.43 1 51 0 1
#> 184 17.77 1 38 0 0
#> 110.1 17.56 1 65 0 1
#> 57 14.46 1 45 0 1
#> 110.2 17.56 1 65 0 1
#> 52 10.42 1 52 0 1
#> 18.1 15.21 1 49 1 0
#> 76 19.22 1 54 0 1
#> 49.1 12.19 1 48 1 0
#> 105 19.75 1 60 0 0
#> 77 7.27 1 67 0 1
#> 130 16.47 1 53 0 1
#> 89 11.44 1 NA 0 0
#> 77.1 7.27 1 67 0 1
#> 153 21.33 1 55 1 0
#> 89.1 11.44 1 NA 0 0
#> 171.1 16.57 1 41 0 1
#> 68 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 164.1 23.60 1 76 0 1
#> 111 17.45 1 47 0 1
#> 187 9.92 1 39 1 0
#> 155 13.08 1 26 0 0
#> 123 13.00 1 44 1 0
#> 179.1 18.63 1 42 0 0
#> 139 21.49 1 63 1 0
#> 183 9.24 1 67 1 0
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 49.2 12.19 1 48 1 0
#> 157 15.10 1 47 0 0
#> 37 12.52 1 57 1 0
#> 129 23.41 1 53 1 0
#> 55 19.34 1 69 0 1
#> 177.1 12.53 1 75 0 0
#> 124 9.73 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 183.1 9.24 1 67 1 0
#> 92.1 22.92 1 47 0 1
#> 6 15.64 1 39 0 0
#> 188 16.16 1 46 0 1
#> 60.1 13.15 1 38 1 0
#> 36 21.19 1 48 0 1
#> 195 11.76 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 192 16.44 1 31 1 0
#> 39 15.59 1 37 0 1
#> 15 22.68 1 48 0 0
#> 49.3 12.19 1 48 1 0
#> 37.1 12.52 1 57 1 0
#> 5.1 16.43 1 51 0 1
#> 107 11.18 1 54 1 0
#> 90 20.94 1 50 0 1
#> 18.2 15.21 1 49 1 0
#> 124.1 9.73 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 69.1 23.23 1 25 0 1
#> 61 10.12 1 36 0 1
#> 154 12.63 1 20 1 0
#> 36.1 21.19 1 48 0 1
#> 50 10.02 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 86 23.81 1 58 0 1
#> 128.1 20.35 1 35 0 1
#> 55.1 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 159.1 10.55 1 50 0 1
#> 153.1 21.33 1 55 1 0
#> 183.2 9.24 1 67 1 0
#> 130.1 16.47 1 53 0 1
#> 70 7.38 1 30 1 0
#> 194 22.40 1 38 0 1
#> 88 18.37 1 47 0 0
#> 150 20.33 1 48 0 0
#> 117.2 17.46 1 26 0 1
#> 180 14.82 1 37 0 0
#> 39.1 15.59 1 37 0 1
#> 101 9.97 1 10 0 1
#> 56 12.21 1 60 0 0
#> 41.1 18.02 1 40 1 0
#> 117.3 17.46 1 26 0 1
#> 42.1 12.43 1 49 0 1
#> 106 16.67 1 49 1 0
#> 183.3 9.24 1 67 1 0
#> 188.1 16.16 1 46 0 1
#> 189 10.51 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 13 14.34 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 91 5.33 1 61 0 1
#> 88.1 18.37 1 47 0 0
#> 14 12.89 1 21 0 0
#> 109 24.00 0 48 0 0
#> 186 24.00 0 45 1 0
#> 38 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 7 24.00 0 37 1 0
#> 186.1 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 131 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 98 24.00 0 34 1 0
#> 1 24.00 0 23 1 0
#> 176 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#> 34 24.00 0 36 0 0
#> 198 24.00 0 66 0 1
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 53 24.00 0 32 0 1
#> 72 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 143 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 11 24.00 0 42 0 1
#> 146 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 185.1 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 3 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 146.1 24.00 0 63 1 0
#> 112.1 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 17.1 24.00 0 38 0 1
#> 46.1 24.00 0 71 0 0
#> 141.1 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 44.1 24.00 0 56 0 0
#> 165.1 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 1.2 24.00 0 23 1 0
#> 75 24.00 0 21 1 0
#> 74 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 122.1 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 122.2 24.00 0 66 0 0
#> 3.1 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 176.1 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 21.1 24.00 0 47 0 0
#> 176.2 24.00 0 43 0 1
#> 141.2 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 121.1 24.00 0 57 1 0
#> 122.3 24.00 0 66 0 0
#> 200.1 24.00 0 64 0 0
#> 12.1 24.00 0 63 0 0
#> 132 24.00 0 55 0 0
#> 141.3 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 21.2 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 102 24.00 0 49 0 0
#> 120.1 24.00 0 68 0 1
#> 156.1 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 118 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 178 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 135.1 24.00 0 58 1 0
#> 73 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0260 NA NA NA
#> 2 age, Cure model -0.00978 NA NA NA
#> 3 grade_ii, Cure model 0.402 NA NA NA
#> 4 grade_iii, Cure model 1.47 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000852 NA NA NA
#> 2 grade_ii, Survival model 0.429 NA NA NA
#> 3 grade_iii, Survival model -0.129 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.026033 -0.009777 0.401580 1.473007
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 244 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.026033429 -0.009777403 0.401580261 1.473006596
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00085246 0.42859816 -0.12871448
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.094184427 0.800111751 0.734021700 0.326854752 0.083535415 0.608521647
#> [7] 0.268648714 0.480909352 0.384807606 0.015537650 0.221313498 0.307439439
#> [13] 0.864145504 0.356203124 0.063665464 0.124658635 0.461216497 0.771783923
#> [19] 0.539528166 0.375185407 0.384807606 0.656825749 0.384807606 0.882490486
#> [25] 0.608521647 0.297595907 0.800111751 0.249727688 0.973082145 0.500424326
#> [31] 0.973082145 0.155451663 0.480909352 0.211823772 0.836575737 0.015537650
#> [37] 0.451355404 0.919403266 0.695601707 0.705268915 0.307439439 0.145365666
#> [43] 0.928577971 0.134951452 0.676407452 0.520061614 0.800111751 0.637316381
#> [49] 0.753012221 0.034747648 0.278334913 0.734021700 0.044751860 0.928577971
#> [55] 0.063665464 0.578791496 0.559106523 0.676407452 0.173897099 0.413309836
#> [61] 0.520061614 0.588724699 0.104270598 0.800111751 0.753012221 0.539528166
#> [67] 0.845861652 0.192654572 0.608521647 0.413309836 0.044751860 0.891726483
#> [73] 0.724479620 0.173897099 0.845861652 0.004703246 0.221313498 0.278334913
#> [79] 0.900976597 0.864145504 0.155451663 0.928577971 0.500424326 0.964114182
#> [85] 0.114396778 0.336719043 0.240118218 0.413309836 0.647068781 0.588724699
#> [91] 0.910183952 0.790627482 0.356203124 0.413309836 0.771783923 0.471111516
#> [97] 0.928577971 0.559106523 0.202349741 0.666605072 0.249727688 0.990991151
#> [103] 0.336719043 0.714873122 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 63 49 177 8 113 18 170 171 110 164 128 179 159
#> 22.77 12.19 12.53 18.43 22.86 15.21 19.54 16.57 17.56 23.60 20.35 18.63 10.55
#> 41 92 175 45 42 5 184 110.1 57 110.2 52 18.1 76
#> 18.02 22.92 21.91 17.42 12.43 16.43 17.77 17.56 14.46 17.56 10.42 15.21 19.22
#> 49.1 105 77 130 77.1 153 171.1 68 43 164.1 111 187 155
#> 12.19 19.75 7.27 16.47 7.27 21.33 16.57 20.62 12.10 23.60 17.45 9.92 13.08
#> 123 179.1 139 183 136 60 85 49.2 157 37 129 55 177.1
#> 13.00 18.63 21.49 9.24 21.83 13.15 16.44 12.19 15.10 12.52 23.41 19.34 12.53
#> 69 183.1 92.1 6 188 60.1 36 117 192 39 15 49.3 37.1
#> 23.23 9.24 22.92 15.64 16.16 13.15 21.19 17.46 16.44 15.59 22.68 12.19 12.52
#> 5.1 107 90 18.2 117.1 69.1 61 154 36.1 107.1 86 128.1 55.1
#> 16.43 11.18 20.94 15.21 17.46 23.23 10.12 12.63 21.19 11.18 23.81 20.35 19.34
#> 145 159.1 153.1 183.2 130.1 70 194 88 150 117.2 180 39.1 101
#> 10.07 10.55 21.33 9.24 16.47 7.38 22.40 18.37 20.33 17.46 14.82 15.59 9.97
#> 56 41.1 117.3 42.1 106 183.3 188.1 32 13 105.1 91 88.1 14
#> 12.21 18.02 17.46 12.43 16.67 9.24 16.16 20.90 14.34 19.75 5.33 18.37 12.89
#> 109 186 38 7 186.1 156 46 165 141 116 131 21 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 1 176 17 119 34 198 12 112 185 191 53 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 121 143 95 11 146 62 185.1 1.1 3 182 146.1 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 17.1 46.1 141.1 131.1 48 147 44.1 165.1 122 1.2 75 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 122.1 109.1 122.2 3.1 135 176.1 33 21.1 176.2 141.2 200 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.3 200.1 12.1 132 141.3 138 21.2 72.1 19 28 94 102 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 2 118 103 178 71 65 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[96]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001216538 0.299552360 0.294069426
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.49742912 0.02072803 0.63921289
#> grade_iii, Cure model
#> 1.44412349
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 129 23.41 1 53 1 0
#> 127 3.53 1 62 0 1
#> 106 16.67 1 49 1 0
#> 169 22.41 1 46 0 0
#> 39 15.59 1 37 0 1
#> 43 12.10 1 61 0 1
#> 108 18.29 1 39 0 1
#> 125 15.65 1 67 1 0
#> 110 17.56 1 65 0 1
#> 133 14.65 1 57 0 0
#> 100 16.07 1 60 0 0
#> 77 7.27 1 67 0 1
#> 30 17.43 1 78 0 0
#> 127.1 3.53 1 62 0 1
#> 136 21.83 1 43 0 1
#> 105 19.75 1 60 0 0
#> 16 8.71 1 71 0 1
#> 117 17.46 1 26 0 1
#> 93 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 128 20.35 1 35 0 1
#> 111 17.45 1 47 0 1
#> 190 20.81 1 42 1 0
#> 50 10.02 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 169.1 22.41 1 46 0 0
#> 29 15.45 1 68 1 0
#> 10 10.53 1 34 0 0
#> 91 5.33 1 61 0 1
#> 76.1 19.22 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 16.1 8.71 1 71 0 1
#> 30.1 17.43 1 78 0 0
#> 136.1 21.83 1 43 0 1
#> 10.1 10.53 1 34 0 0
#> 187 9.92 1 39 1 0
#> 16.2 8.71 1 71 0 1
#> 26 15.77 1 49 0 1
#> 188 16.16 1 46 0 1
#> 154 12.63 1 20 1 0
#> 158 20.14 1 74 1 0
#> 159 10.55 1 50 0 1
#> 155 13.08 1 26 0 0
#> 107 11.18 1 54 1 0
#> 179 18.63 1 42 0 0
#> 166 19.98 1 48 0 0
#> 136.2 21.83 1 43 0 1
#> 158.1 20.14 1 74 1 0
#> 117.1 17.46 1 26 0 1
#> 166.1 19.98 1 48 0 0
#> 78 23.88 1 43 0 0
#> 41 18.02 1 40 1 0
#> 51 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 189.1 10.51 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 125.1 15.65 1 67 1 0
#> 171 16.57 1 41 0 1
#> 77.1 7.27 1 67 0 1
#> 69 23.23 1 25 0 1
#> 140 12.68 1 59 1 0
#> 124 9.73 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 197 21.60 1 69 1 0
#> 157 15.10 1 47 0 0
#> 110.1 17.56 1 65 0 1
#> 166.2 19.98 1 48 0 0
#> 14 12.89 1 21 0 0
#> 170 19.54 1 43 0 1
#> 10.2 10.53 1 34 0 0
#> 123 13.00 1 44 1 0
#> 105.1 19.75 1 60 0 0
#> 153 21.33 1 55 1 0
#> 133.1 14.65 1 57 0 0
#> 13.1 14.34 1 54 0 1
#> 41.1 18.02 1 40 1 0
#> 180 14.82 1 37 0 0
#> 181 16.46 1 45 0 1
#> 100.1 16.07 1 60 0 0
#> 159.1 10.55 1 50 0 1
#> 197.1 21.60 1 69 1 0
#> 158.2 20.14 1 74 1 0
#> 108.1 18.29 1 39 0 1
#> 93.1 10.33 1 52 0 1
#> 183 9.24 1 67 1 0
#> 88 18.37 1 47 0 0
#> 86 23.81 1 58 0 1
#> 199 19.81 1 NA 0 1
#> 139 21.49 1 63 1 0
#> 124.1 9.73 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 18 15.21 1 49 1 0
#> 13.2 14.34 1 54 0 1
#> 55.1 19.34 1 69 0 1
#> 192.1 16.44 1 31 1 0
#> 100.2 16.07 1 60 0 0
#> 43.1 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 92 22.92 1 47 0 1
#> 194 22.40 1 38 0 1
#> 37.2 12.52 1 57 1 0
#> 41.2 18.02 1 40 1 0
#> 134 17.81 1 47 1 0
#> 159.2 10.55 1 50 0 1
#> 124.2 9.73 1 NA 1 0
#> 134.1 17.81 1 47 1 0
#> 152 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 132 24.00 0 55 0 0
#> 35 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 95 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 11 24.00 0 42 0 1
#> 178 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 172 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 132.1 24.00 0 55 0 0
#> 80 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 46.1 24.00 0 71 0 0
#> 62 24.00 0 71 0 0
#> 47.1 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 131 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 132.2 24.00 0 55 0 0
#> 196 24.00 0 19 0 0
#> 54 24.00 0 53 1 0
#> 116 24.00 0 58 0 1
#> 54.1 24.00 0 53 1 0
#> 172.1 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 44.1 24.00 0 56 0 0
#> 116.1 24.00 0 58 0 1
#> 71 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 116.2 24.00 0 58 0 1
#> 143 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 67 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 148.1 24.00 0 61 1 0
#> 75 24.00 0 21 1 0
#> 75.1 24.00 0 21 1 0
#> 152.1 24.00 0 36 0 1
#> 172.2 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 196.1 24.00 0 19 0 0
#> 182.1 24.00 0 35 0 0
#> 135 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 64.1 24.00 0 43 0 0
#> 196.2 24.00 0 19 0 0
#> 22.1 24.00 0 52 1 0
#> 147 24.00 0 76 1 0
#> 64.2 24.00 0 43 0 0
#> 44.2 24.00 0 56 0 0
#> 87 24.00 0 27 0 0
#> 9 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 62.1 24.00 0 71 0 0
#> 27.1 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 121.1 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 64.3 24.00 0 43 0 0
#> 119.1 24.00 0 17 0 0
#> 27.2 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 116.3 24.00 0 58 0 1
#> 132.3 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 80.1 24.00 0 41 0 0
#> 47.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.50 NA NA NA
#> 2 age, Cure model 0.0207 NA NA NA
#> 3 grade_ii, Cure model 0.639 NA NA NA
#> 4 grade_iii, Cure model 1.44 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00122 NA NA NA
#> 2 grade_ii, Survival model 0.300 NA NA NA
#> 3 grade_iii, Survival model 0.294 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.49743 0.02073 0.63921 1.44412
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 244.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.49742912 0.02072803 0.63921289 1.44412349
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001216538 0.299552360 0.294069426
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.39822508 0.07907672 0.98575406 0.57179640 0.12818372 0.67237851
#> [7] 0.83077374 0.43702427 0.65600431 0.51055413 0.71304099 0.62284723
#> [13] 0.96417341 0.55448683 0.98575406 0.17119219 0.33825274 0.93519650
#> [19] 0.52825781 0.89824377 0.75277544 0.72912292 0.36901810 0.26606077
#> [25] 0.54573605 0.25466432 0.80011830 0.12818372 0.68057554 0.87591849
#> [31] 0.97855851 0.39822508 0.80011830 0.36901810 0.93519650 0.55448683
#> [37] 0.17119219 0.87591849 0.91308359 0.93519650 0.64766837 0.61443543
#> [43] 0.79228926 0.27726523 0.85356919 0.76070897 0.84596791 0.41752894
#> [49] 0.30784849 0.17119219 0.27726523 0.52825781 0.30784849 0.01550624
#> [55] 0.46541691 0.45594996 0.82307864 0.91308359 0.65600431 0.58046060
#> [61] 0.96417341 0.09650114 0.78443052 0.59763123 0.20752273 0.69683670
#> [67] 0.51055413 0.30784849 0.77653622 0.35874469 0.87591849 0.76863985
#> [73] 0.33825274 0.24304970 0.71304099 0.72912292 0.46541691 0.70494099
#> [79] 0.58907203 0.62284723 0.85356919 0.20752273 0.27726523 0.43702427
#> [85] 0.89824377 0.92782404 0.42728314 0.04005590 0.23118426 0.05981697
#> [91] 0.68872686 0.72912292 0.36901810 0.59763123 0.62284723 0.83077374
#> [97] 0.95690421 0.11280749 0.15675006 0.80011830 0.46541691 0.49256846
#> [103] 0.85356919 0.49256846 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 76 129 127 106 169 39 43 108 125 110 133 100 77
#> 19.22 23.41 3.53 16.67 22.41 15.59 12.10 18.29 15.65 17.56 14.65 16.07 7.27
#> 30 127.1 136 105 16 117 93 60 13 58 128 111 190
#> 17.43 3.53 21.83 19.75 8.71 17.46 10.33 13.15 14.34 19.34 20.35 17.45 20.81
#> 37 169.1 29 10 91 76.1 37.1 55 16.1 30.1 136.1 10.1 187
#> 12.52 22.41 15.45 10.53 5.33 19.22 12.52 19.34 8.71 17.43 21.83 10.53 9.92
#> 16.2 26 188 154 158 159 155 107 179 166 136.2 158.1 117.1
#> 8.71 15.77 16.16 12.63 20.14 10.55 13.08 11.18 18.63 19.98 21.83 20.14 17.46
#> 166.1 78 41 51 42 187.1 125.1 171 77.1 69 140 192 197
#> 19.98 23.88 18.02 18.23 12.43 9.92 15.65 16.57 7.27 23.23 12.68 16.44 21.60
#> 157 110.1 166.2 14 170 10.2 123 105.1 153 133.1 13.1 41.1 180
#> 15.10 17.56 19.98 12.89 19.54 10.53 13.00 19.75 21.33 14.65 14.34 18.02 14.82
#> 181 100.1 159.1 197.1 158.2 108.1 93.1 183 88 86 139 168 18
#> 16.46 16.07 10.55 21.60 20.14 18.29 10.33 9.24 18.37 23.81 21.49 23.72 15.21
#> 13.2 55.1 192.1 100.2 43.1 70 92 194 37.2 41.2 134 159.2 134.1
#> 14.34 19.34 16.44 16.07 12.10 7.38 22.92 22.40 12.52 18.02 17.81 10.55 17.81
#> 152 83 33 182 173 132 35 112 95 118 185 47 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 28 172 46 121 19 142 132.1 80 22 119 21 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 47.1 104 53 131 17 132.2 196 54 116 54.1 172.1 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 116.1 71 98 116.2 143 178.1 191 161 67 148 148.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 152.1 172.2 64 151 196.1 182.1 135 156 27 64.1 196.2 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 64.2 44.2 87 9 34 62.1 27.1 162 72 121.1 82 64.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 27.2 7 116.3 132.3 174 138 165 80.1 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[97]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005727053 0.756358623 0.566553275
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.97869952 0.02351341 -0.33936728
#> grade_iii, Cure model
#> 0.66172167
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 52 10.42 1 52 0 1
#> 49 12.19 1 48 1 0
#> 130 16.47 1 53 0 1
#> 55 19.34 1 69 0 1
#> 61 10.12 1 36 0 1
#> 108 18.29 1 39 0 1
#> 50 10.02 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 76 19.22 1 54 0 1
#> 157 15.10 1 47 0 0
#> 181 16.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 175 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 179 18.63 1 42 0 0
#> 199 19.81 1 NA 0 1
#> 180 14.82 1 37 0 0
#> 159 10.55 1 50 0 1
#> 39 15.59 1 37 0 1
#> 166 19.98 1 48 0 0
#> 188 16.16 1 46 0 1
#> 139 21.49 1 63 1 0
#> 23 16.92 1 61 0 0
#> 36 21.19 1 48 0 1
#> 153 21.33 1 55 1 0
#> 166.1 19.98 1 48 0 0
#> 183 9.24 1 67 1 0
#> 136 21.83 1 43 0 1
#> 18 15.21 1 49 1 0
#> 96 14.54 1 33 0 1
#> 15 22.68 1 48 0 0
#> 159.1 10.55 1 50 0 1
#> 168 23.72 1 70 0 0
#> 93 10.33 1 52 0 1
#> 123 13.00 1 44 1 0
#> 113 22.86 1 34 0 0
#> 150.1 20.33 1 48 0 0
#> 77 7.27 1 67 0 1
#> 187 9.92 1 39 1 0
#> 177 12.53 1 75 0 0
#> 91 5.33 1 61 0 1
#> 158 20.14 1 74 1 0
#> 29 15.45 1 68 1 0
#> 127 3.53 1 62 0 1
#> 42 12.43 1 49 0 1
#> 25 6.32 1 34 1 0
#> 91.1 5.33 1 61 0 1
#> 157.1 15.10 1 47 0 0
#> 25.1 6.32 1 34 1 0
#> 124 9.73 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 167 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 123.1 13.00 1 44 1 0
#> 134 17.81 1 47 1 0
#> 68 20.62 1 44 0 0
#> 16 8.71 1 71 0 1
#> 18.1 15.21 1 49 1 0
#> 180.1 14.82 1 37 0 0
#> 78 23.88 1 43 0 0
#> 110 17.56 1 65 0 1
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 18.2 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 145 10.07 1 65 1 0
#> 58 19.34 1 39 0 0
#> 69 23.23 1 25 0 1
#> 24 23.89 1 38 0 0
#> 108.1 18.29 1 39 0 1
#> 63 22.77 1 31 1 0
#> 59.1 10.16 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 51 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 6 15.64 1 39 0 0
#> 25.2 6.32 1 34 1 0
#> 124.1 9.73 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 37 12.52 1 57 1 0
#> 6.1 15.64 1 39 0 0
#> 42.1 12.43 1 49 0 1
#> 159.2 10.55 1 50 0 1
#> 190 20.81 1 42 1 0
#> 10 10.53 1 34 0 0
#> 181.1 16.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 59.2 10.16 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 92 22.92 1 47 0 1
#> 26 15.77 1 49 0 1
#> 123.2 13.00 1 44 1 0
#> 179.1 18.63 1 42 0 0
#> 61.1 10.12 1 36 0 1
#> 194 22.40 1 38 0 1
#> 180.2 14.82 1 37 0 0
#> 13 14.34 1 54 0 1
#> 184 17.77 1 38 0 0
#> 93.1 10.33 1 52 0 1
#> 139.1 21.49 1 63 1 0
#> 99.1 21.19 1 38 0 1
#> 26.1 15.77 1 49 0 1
#> 139.2 21.49 1 63 1 0
#> 133 14.65 1 57 0 0
#> 51.1 18.23 1 83 0 1
#> 15.2 22.68 1 48 0 0
#> 52.1 10.42 1 52 0 1
#> 177.1 12.53 1 75 0 0
#> 70 7.38 1 30 1 0
#> 136.1 21.83 1 43 0 1
#> 187.1 9.92 1 39 1 0
#> 148 24.00 0 61 1 0
#> 73 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 27 24.00 0 63 1 0
#> 83 24.00 0 6 0 0
#> 44 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 146 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 87.1 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 148.1 24.00 0 61 1 0
#> 200 24.00 0 64 0 0
#> 116.1 24.00 0 58 0 1
#> 160.1 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 28 24.00 0 67 1 0
#> 176 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 34 24.00 0 36 0 0
#> 174 24.00 0 49 1 0
#> 22 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 1 24.00 0 23 1 0
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 200.1 24.00 0 64 0 0
#> 176.1 24.00 0 43 0 1
#> 44.1 24.00 0 56 0 0
#> 173 24.00 0 19 0 1
#> 75 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 152 24.00 0 36 0 1
#> 174.1 24.00 0 49 1 0
#> 126 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 200.2 24.00 0 64 0 0
#> 1.1 24.00 0 23 1 0
#> 35.1 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 160.2 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 12 24.00 0 63 0 0
#> 185.1 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 84 24.00 0 39 0 1
#> 82 24.00 0 34 0 0
#> 178 24.00 0 52 1 0
#> 135.1 24.00 0 58 1 0
#> 152.1 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 74.1 24.00 0 43 0 1
#> 178.1 24.00 0 52 1 0
#> 174.2 24.00 0 49 1 0
#> 1.2 24.00 0 23 1 0
#> 65 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 1.3 24.00 0 23 1 0
#> 178.2 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 83.1 24.00 0 6 0 0
#> 126.1 24.00 0 48 0 0
#> 27.1 24.00 0 63 1 0
#> 109 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 75.1 24.00 0 21 1 0
#> 172.1 24.00 0 41 0 0
#> 178.3 24.00 0 52 1 0
#> 119.1 24.00 0 17 0 0
#> 87.2 24.00 0 27 0 0
#> 1.4 24.00 0 23 1 0
#> 119.2 24.00 0 17 0 0
#> 38 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 121 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.979 NA NA NA
#> 2 age, Cure model 0.0235 NA NA NA
#> 3 grade_ii, Cure model -0.339 NA NA NA
#> 4 grade_iii, Cure model 0.662 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00573 NA NA NA
#> 2 grade_ii, Survival model 0.756 NA NA NA
#> 3 grade_iii, Survival model 0.567 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97870 0.02351 -0.33937 0.66172
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 250.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97869952 0.02351341 -0.33936728 0.66172167
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005727053 0.756358623 0.566553275
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.91254028 0.88753595 0.66429065 0.53327781 0.93200855 0.59460115
#> [7] 0.68576459 0.55159717 0.78220072 0.67160609 0.72644456 0.33621687
#> [13] 0.48468602 0.57767973 0.79392166 0.89264727 0.74576662 0.51435184
#> [19] 0.70652518 0.38457394 0.65686173 0.43274369 0.42093058 0.51435184
#> [25] 0.95558641 0.35387706 0.76460420 0.81718170 0.26407230 0.89264727
#> [31] 0.12840083 0.92234496 0.82870074 0.21902607 0.48468602 0.96931242
#> [37] 0.94629266 0.85605593 0.98699199 0.50468664 0.75843251 0.99567672
#> [43] 0.87723600 0.97382025 0.98699199 0.78220072 0.97382025 0.85064441
#> [49] 0.75215118 0.84518465 0.82870074 0.62655757 0.47444531 0.96019683
#> [55] 0.76460420 0.79392166 0.08637540 0.64188466 0.56062248 0.56062248
#> [61] 0.76460420 0.69966858 0.94155675 0.53327781 0.16471071 0.03863962
#> [67] 0.59460115 0.24315022 0.68576459 0.61096242 0.64939751 0.73292320
#> [73] 0.97382025 0.26407230 0.86677229 0.73292320 0.87723600 0.89264727
#> [79] 0.46414088 0.90755087 0.67160609 0.43274369 0.86677229 0.19432040
#> [85] 0.71329680 0.82870074 0.57767973 0.93200855 0.31829409 0.79392166
#> [91] 0.82296945 0.63423237 0.92234496 0.38457394 0.43274369 0.71329680
#> [97] 0.38457394 0.81134731 0.61096242 0.26407230 0.91254028 0.85605593
#> [103] 0.96477110 0.35387706 0.94629266 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 52 49 130 55 61 108 192 76 157 181 125 175 150
#> 10.42 12.19 16.47 19.34 10.12 18.29 16.44 19.22 15.10 16.46 15.65 21.91 20.33
#> 179 180 159 39 166 188 139 23 36 153 166.1 183 136
#> 18.63 14.82 10.55 15.59 19.98 16.16 21.49 16.92 21.19 21.33 19.98 9.24 21.83
#> 18 96 15 159.1 168 93 123 113 150.1 77 187 177 91
#> 15.21 14.54 22.68 10.55 23.72 10.33 13.00 22.86 20.33 7.27 9.92 12.53 5.33
#> 158 29 127 42 25 91.1 157.1 25.1 154 167 140 123.1 134
#> 20.14 15.45 3.53 12.43 6.32 5.33 15.10 6.32 12.63 15.55 12.68 13.00 17.81
#> 68 16 18.1 180.1 78 110 97 97.1 18.2 79 145 58 69
#> 20.62 8.71 15.21 14.82 23.88 17.56 19.14 19.14 15.21 16.23 10.07 19.34 23.23
#> 24 108.1 63 85 51 30 6 25.2 15.1 37 6.1 42.1 159.2
#> 23.89 18.29 22.77 16.44 18.23 17.43 15.64 6.32 22.68 12.52 15.64 12.43 10.55
#> 190 10 181.1 99 37.1 92 26 123.2 179.1 61.1 194 180.2 13
#> 20.81 10.53 16.46 21.19 12.52 22.92 15.77 13.00 18.63 10.12 22.40 14.82 14.34
#> 184 93.1 139.1 99.1 26.1 139.2 133 51.1 15.2 52.1 177.1 70 136.1
#> 17.77 10.33 21.49 21.19 15.77 21.49 14.65 18.23 22.68 10.42 12.53 7.38 21.83
#> 187.1 148 53 27 83 44 196 146 87 35 185 160 80
#> 9.92 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 116 148.1 200 116.1 160.1 119 28 176 135 34 174 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 67 1 137 47 95 200.1 176.1 44.1 173 75 143 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 174.1 126 147 200.2 1.1 35.1 112 3 120 160.2 120.1 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 185.1 191 84 82 178 135.1 152.1 172 74.1 178.1 174.2 1.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 48 1.3 178.2 95.1 83.1 126.1 27.1 109 28.1 75.1 172.1 178.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 87.2 1.4 119.2 38 2 121 104 104.1 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[98]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006447627 0.546054753 0.232304235
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.370460394 0.004790441 0.387019990
#> grade_iii, Cure model
#> 0.699596122
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 8 18.43 1 32 0 0
#> 189 10.51 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 32 20.90 1 37 1 0
#> 15 22.68 1 48 0 0
#> 150 20.33 1 48 0 0
#> 108 18.29 1 39 0 1
#> 106 16.67 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 130 16.47 1 53 0 1
#> 25 6.32 1 34 1 0
#> 154 12.63 1 20 1 0
#> 181 16.46 1 45 0 1
#> 188 16.16 1 46 0 1
#> 52 10.42 1 52 0 1
#> 85 16.44 1 36 0 0
#> 63 22.77 1 31 1 0
#> 164 23.60 1 76 0 1
#> 149 8.37 1 33 1 0
#> 183 9.24 1 67 1 0
#> 97 19.14 1 65 0 1
#> 187 9.92 1 39 1 0
#> 90 20.94 1 50 0 1
#> 99 21.19 1 38 0 1
#> 10 10.53 1 34 0 0
#> 16 8.71 1 71 0 1
#> 50 10.02 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 114 13.68 1 NA 0 0
#> 26 15.77 1 49 0 1
#> 190 20.81 1 42 1 0
#> 23 16.92 1 61 0 0
#> 93 10.33 1 52 0 1
#> 77 7.27 1 67 0 1
#> 195 11.76 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 32.1 20.90 1 37 1 0
#> 136 21.83 1 43 0 1
#> 86 23.81 1 58 0 1
#> 164.1 23.60 1 76 0 1
#> 85.1 16.44 1 36 0 0
#> 99.1 21.19 1 38 0 1
#> 55 19.34 1 69 0 1
#> 140 12.68 1 59 1 0
#> 129 23.41 1 53 1 0
#> 96 14.54 1 33 0 1
#> 40 18.00 1 28 1 0
#> 86.1 23.81 1 58 0 1
#> 181.1 16.46 1 45 0 1
#> 177 12.53 1 75 0 0
#> 125 15.65 1 67 1 0
#> 155 13.08 1 26 0 0
#> 58 19.34 1 39 0 0
#> 81 14.06 1 34 0 0
#> 190.1 20.81 1 42 1 0
#> 164.2 23.60 1 76 0 1
#> 170 19.54 1 43 0 1
#> 168 23.72 1 70 0 0
#> 49 12.19 1 48 1 0
#> 49.1 12.19 1 48 1 0
#> 192 16.44 1 31 1 0
#> 5 16.43 1 51 0 1
#> 6 15.64 1 39 0 0
#> 78 23.88 1 43 0 0
#> 175 21.91 1 43 0 0
#> 166 19.98 1 48 0 0
#> 123 13.00 1 44 1 0
#> 158 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 139 21.49 1 63 1 0
#> 155.1 13.08 1 26 0 0
#> 106.1 16.67 1 49 1 0
#> 30 17.43 1 78 0 0
#> 77.1 7.27 1 67 0 1
#> 15.1 22.68 1 48 0 0
#> 85.2 16.44 1 36 0 0
#> 136.1 21.83 1 43 0 1
#> 111 17.45 1 47 0 1
#> 37.1 12.52 1 57 1 0
#> 150.1 20.33 1 48 0 0
#> 24 23.89 1 38 0 0
#> 125.1 15.65 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 106.2 16.67 1 49 1 0
#> 10.1 10.53 1 34 0 0
#> 23.1 16.92 1 61 0 0
#> 23.2 16.92 1 61 0 0
#> 50.1 10.02 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 43 12.10 1 61 0 1
#> 154.1 12.63 1 20 1 0
#> 136.2 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 177.1 12.53 1 75 0 0
#> 23.3 16.92 1 61 0 0
#> 154.2 12.63 1 20 1 0
#> 197 21.60 1 69 1 0
#> 66 22.13 1 53 0 0
#> 99.2 21.19 1 38 0 1
#> 61 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 134 17.81 1 47 1 0
#> 179.1 18.63 1 42 0 0
#> 26.1 15.77 1 49 0 1
#> 5.1 16.43 1 51 0 1
#> 49.2 12.19 1 48 1 0
#> 158.1 20.14 1 74 1 0
#> 170.1 19.54 1 43 0 1
#> 169 22.41 1 46 0 0
#> 42 12.43 1 49 0 1
#> 129.1 23.41 1 53 1 0
#> 24.1 23.89 1 38 0 0
#> 132 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 35 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 48 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 98 24.00 0 34 1 0
#> 138 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 64 24.00 0 43 0 0
#> 143 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 132.1 24.00 0 55 0 0
#> 102 24.00 0 49 0 0
#> 19 24.00 0 57 0 1
#> 126 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 74 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 3 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 115 24.00 0 NA 1 0
#> 116 24.00 0 58 0 1
#> 44.1 24.00 0 56 0 0
#> 102.1 24.00 0 49 0 0
#> 172 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 132.2 24.00 0 55 0 0
#> 87 24.00 0 27 0 0
#> 35.2 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 162.1 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 95 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 116.1 24.00 0 58 0 1
#> 62 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 161.1 24.00 0 45 0 0
#> 95.1 24.00 0 68 0 1
#> 98.1 24.00 0 34 1 0
#> 132.3 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 137 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 44.2 24.00 0 56 0 0
#> 12 24.00 0 63 0 0
#> 80 24.00 0 41 0 0
#> 142.1 24.00 0 53 0 0
#> 146 24.00 0 63 1 0
#> 98.2 24.00 0 34 1 0
#> 1 24.00 0 23 1 0
#> 126.1 24.00 0 48 0 0
#> 161.2 24.00 0 45 0 0
#> 115.1 24.00 0 NA 1 0
#> 147 24.00 0 76 1 0
#> 22 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 82 24.00 0 34 0 0
#> 82.1 24.00 0 34 0 0
#> 31.1 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 12.1 24.00 0 63 0 0
#> 174 24.00 0 49 1 0
#> 28.1 24.00 0 67 1 0
#> 103.1 24.00 0 56 1 0
#> 19.1 24.00 0 57 0 1
#> 103.2 24.00 0 56 1 0
#> 185 24.00 0 44 1 0
#> 11.2 24.00 0 42 0 1
#> 34 24.00 0 36 0 0
#> 19.2 24.00 0 57 0 1
#> 161.3 24.00 0 45 0 0
#> 178.1 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.370 NA NA NA
#> 2 age, Cure model 0.00479 NA NA NA
#> 3 grade_ii, Cure model 0.387 NA NA NA
#> 4 grade_iii, Cure model 0.700 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00645 NA NA NA
#> 2 grade_ii, Survival model 0.546 NA NA NA
#> 3 grade_iii, Survival model 0.232 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.37046 0.00479 0.38702 0.69960
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 258.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.370460394 0.004790441 0.387019990 0.699596122
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006447627 0.546054753 0.232304235
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.402625432 0.804927344 0.244234558 0.112054846 0.280881391 0.422139724
#> [7] 0.519715588 0.548809015 0.990245435 0.756336960 0.558701877 0.636873581
#> [13] 0.902178896 0.578351254 0.103063162 0.049478477 0.961001366 0.941428623
#> [19] 0.373917209 0.931640134 0.234519032 0.206658636 0.882679241 0.951204832
#> [25] 0.093735617 0.646838963 0.262760049 0.480732395 0.911992419 0.970758559
#> [31] 0.383491639 0.244234558 0.159136331 0.024431281 0.049478477 0.578351254
#> [37] 0.206658636 0.345621129 0.746353843 0.075886157 0.696401618 0.441781365
#> [43] 0.024431281 0.558701877 0.785307038 0.666664874 0.716387346 0.345621129
#> [49] 0.706380567 0.262760049 0.049478477 0.327066504 0.039988219 0.834286191
#> [55] 0.834286191 0.578351254 0.617117850 0.686419850 0.015885945 0.149276473
#> [61] 0.317677639 0.736346614 0.299319674 0.431931369 0.196939574 0.716387346
#> [67] 0.519715588 0.470942226 0.970758559 0.112054846 0.578351254 0.159136331
#> [73] 0.461231844 0.804927344 0.280881391 0.004427348 0.666664874 0.519715588
#> [79] 0.882679241 0.480732395 0.480732395 0.412352396 0.863165475 0.756336960
#> [85] 0.159136331 0.364384378 0.785307038 0.480732395 0.756336960 0.187148092
#> [91] 0.139571995 0.206658636 0.921816286 0.872917660 0.451535410 0.383491639
#> [97] 0.646838963 0.617117850 0.834286191 0.299319674 0.327066504 0.130059158
#> [103] 0.824454638 0.075886157 0.004427348 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 8 37 32 15 150 108 106 130 25 154 181 188 52
#> 18.43 12.52 20.90 22.68 20.33 18.29 16.67 16.47 6.32 12.63 16.46 16.16 10.42
#> 85 63 164 149 183 97 187 90 99 10 16 69 26
#> 16.44 22.77 23.60 8.37 9.24 19.14 9.92 20.94 21.19 10.53 8.71 23.23 15.77
#> 190 23 93 77 179 32.1 136 86 164.1 85.1 99.1 55 140
#> 20.81 16.92 10.33 7.27 18.63 20.90 21.83 23.81 23.60 16.44 21.19 19.34 12.68
#> 129 96 40 86.1 181.1 177 125 155 58 81 190.1 164.2 170
#> 23.41 14.54 18.00 23.81 16.46 12.53 15.65 13.08 19.34 14.06 20.81 23.60 19.54
#> 168 49 49.1 192 5 6 78 175 166 123 158 51 139
#> 23.72 12.19 12.19 16.44 16.43 15.64 23.88 21.91 19.98 13.00 20.14 18.23 21.49
#> 155.1 106.1 30 77.1 15.1 85.2 136.1 111 37.1 150.1 24 125.1 106.2
#> 13.08 16.67 17.43 7.27 22.68 16.44 21.83 17.45 12.52 20.33 23.89 15.65 16.67
#> 10.1 23.1 23.2 88 43 154.1 136.2 76 177.1 23.3 154.2 197 66
#> 10.53 16.92 16.92 18.37 12.10 12.63 21.83 19.22 12.53 16.92 12.63 21.60 22.13
#> 99.2 61 159 134 179.1 26.1 5.1 49.2 158.1 170.1 169 42 129.1
#> 21.19 10.12 10.55 17.81 18.63 15.77 16.43 12.19 20.14 19.54 22.41 12.43 23.41
#> 24.1 132 44 35 17 191 182 48 31 98 138 35.1 162
#> 23.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 64 143 119 132.1 102 19 126 198 74 112 3 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 28 116 44.1 102.1 172 109 132.2 87 35.2 118 103 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 95 178 116.1 62 7 142 38 74.1 11 161.1 95.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.3 193 137 144 53 44.2 12 80 142.1 146 98.2 1 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.2 147 22 75 82 82.1 31.1 160 11.1 12.1 174 28.1 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 103.2 185 11.2 34 19.2 161.3 178.1 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[99]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02244959 0.55332938 0.36274389
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 5.174248e-02 -3.699002e-05 -2.323531e-01
#> grade_iii, Cure model
#> 6.704864e-01
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 155 13.08 1 26 0 0
#> 180 14.82 1 37 0 0
#> 23 16.92 1 61 0 0
#> 180.1 14.82 1 37 0 0
#> 155.1 13.08 1 26 0 0
#> 181 16.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 79 16.23 1 54 1 0
#> 45 17.42 1 54 0 1
#> 123 13.00 1 44 1 0
#> 101 9.97 1 10 0 1
#> 97 19.14 1 65 0 1
#> 110 17.56 1 65 0 1
#> 49 12.19 1 48 1 0
#> 18 15.21 1 49 1 0
#> 117 17.46 1 26 0 1
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 24 23.89 1 38 0 0
#> 96 14.54 1 33 0 1
#> 177 12.53 1 75 0 0
#> 199 19.81 1 NA 0 1
#> 92 22.92 1 47 0 1
#> 88 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 167 15.55 1 56 1 0
#> 88.1 18.37 1 47 0 0
#> 15 22.68 1 48 0 0
#> 139.1 21.49 1 63 1 0
#> 66 22.13 1 53 0 0
#> 154 12.63 1 20 1 0
#> 199.1 19.81 1 NA 0 1
#> 133 14.65 1 57 0 0
#> 63 22.77 1 31 1 0
#> 49.1 12.19 1 48 1 0
#> 78 23.88 1 43 0 0
#> 96.1 14.54 1 33 0 1
#> 26 15.77 1 49 0 1
#> 26.1 15.77 1 49 0 1
#> 45.1 17.42 1 54 0 1
#> 113 22.86 1 34 0 0
#> 97.1 19.14 1 65 0 1
#> 168 23.72 1 70 0 0
#> 188 16.16 1 46 0 1
#> 145 10.07 1 65 1 0
#> 106 16.67 1 49 1 0
#> 10 10.53 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 15.1 22.68 1 48 0 0
#> 23.1 16.92 1 61 0 0
#> 111 17.45 1 47 0 1
#> 40 18.00 1 28 1 0
#> 25 6.32 1 34 1 0
#> 189 10.51 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 56.1 12.21 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 15.2 22.68 1 48 0 0
#> 169 22.41 1 46 0 0
#> 89 11.44 1 NA 0 0
#> 10.1 10.53 1 34 0 0
#> 26.2 15.77 1 49 0 1
#> 85 16.44 1 36 0 0
#> 40.1 18.00 1 28 1 0
#> 101.1 9.97 1 10 0 1
#> 123.1 13.00 1 44 1 0
#> 168.1 23.72 1 70 0 0
#> 110.1 17.56 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 184 17.77 1 38 0 0
#> 85.1 16.44 1 36 0 0
#> 10.2 10.53 1 34 0 0
#> 127 3.53 1 62 0 1
#> 170 19.54 1 43 0 1
#> 101.2 9.97 1 10 0 1
#> 36 21.19 1 48 0 1
#> 105 19.75 1 60 0 0
#> 189.1 10.51 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 164.1 23.60 1 76 0 1
#> 85.2 16.44 1 36 0 0
#> 197 21.60 1 69 1 0
#> 55 19.34 1 69 0 1
#> 180.2 14.82 1 37 0 0
#> 76 19.22 1 54 0 1
#> 16 8.71 1 71 0 1
#> 10.3 10.53 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 36.1 21.19 1 48 0 1
#> 5 16.43 1 51 0 1
#> 175 21.91 1 43 0 0
#> 55.1 19.34 1 69 0 1
#> 180.3 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 128.1 20.35 1 35 0 1
#> 111.1 17.45 1 47 0 1
#> 10.4 10.53 1 34 0 0
#> 108 18.29 1 39 0 1
#> 32 20.90 1 37 1 0
#> 195.1 11.76 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 36.2 21.19 1 48 0 1
#> 140 12.68 1 59 1 0
#> 180.4 14.82 1 37 0 0
#> 93 10.33 1 52 0 1
#> 175.1 21.91 1 43 0 0
#> 192 16.44 1 31 1 0
#> 187 9.92 1 39 1 0
#> 180.5 14.82 1 37 0 0
#> 48 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 178 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 172 24.00 0 41 0 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 35 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 174 24.00 0 49 1 0
#> 186 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 31 24.00 0 36 0 1
#> 122.1 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 196 24.00 0 19 0 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 109 24.00 0 48 0 0
#> 174.1 24.00 0 49 1 0
#> 12 24.00 0 63 0 0
#> 109.1 24.00 0 48 0 0
#> 48.1 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 75 24.00 0 21 1 0
#> 83.1 24.00 0 6 0 0
#> 82 24.00 0 34 0 0
#> 75.1 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 126 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 162.1 24.00 0 51 0 0
#> 152.1 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 174.2 24.00 0 49 1 0
#> 94 24.00 0 51 0 1
#> 74 24.00 0 43 0 1
#> 126.1 24.00 0 48 0 0
#> 163.1 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 122.2 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#> 103 24.00 0 56 1 0
#> 131 24.00 0 66 0 0
#> 17.1 24.00 0 38 0 1
#> 182.1 24.00 0 35 0 0
#> 3 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 44.1 24.00 0 56 0 0
#> 115 24.00 0 NA 1 0
#> 44.2 24.00 0 56 0 0
#> 116.1 24.00 0 58 0 1
#> 65.1 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 65.2 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 65.3 24.00 0 57 1 0
#> 53.1 24.00 0 32 0 1
#> 12.1 24.00 0 63 0 0
#> 87 24.00 0 27 0 0
#> 53.2 24.00 0 32 0 1
#> 122.3 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 38.1 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 27 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0517 NA NA NA
#> 2 age, Cure model -0.0000370 NA NA NA
#> 3 grade_ii, Cure model -0.232 NA NA NA
#> 4 grade_iii, Cure model 0.670 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0224 NA NA NA
#> 2 grade_ii, Survival model 0.553 NA NA NA
#> 3 grade_iii, Survival model 0.363 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 5.174e-02 -3.699e-05 -2.324e-01 6.705e-01
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 256.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 5.174248e-02 -3.699002e-05 -2.323531e-01 6.704864e-01
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02244959 0.55332938 0.36274389
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 6.592745e-01 5.338150e-01 4.081506e-01 2.067388e-01 4.081506e-01
#> [6] 5.338150e-01 2.359691e-01 9.428328e-01 2.986245e-01 1.887633e-01
#> [11] 5.643887e-01 8.509241e-01 9.083782e-02 1.473345e-01 6.925694e-01
#> [16] 3.821270e-01 1.633958e-01 1.830634e-02 5.366474e-02 4.206091e-04
#> [21] 2.269419e-06 5.039966e-01 6.430266e-01 1.323815e-03 1.037161e-01
#> [26] 4.535644e-02 3.694349e-01 1.037161e-01 3.952652e-03 1.830634e-02
#> [31] 9.285750e-03 6.115801e-01 4.891413e-01 2.988873e-03 6.925694e-01
#> [36] 2.372188e-05 5.039966e-01 3.215582e-01 3.215582e-01 1.887633e-01
#> [41] 2.066814e-03 9.083782e-02 8.191023e-05 3.099878e-01 8.322068e-01
#> [46] 2.259611e-01 7.265306e-01 6.115801e-01 3.952652e-03 2.067388e-01
#> [51] 1.717173e-01 1.251408e-01 9.617614e-01 2.413435e-02 6.592745e-01
#> [56] 3.952652e-03 7.588809e-03 7.265306e-01 3.215582e-01 2.461836e-01
#> [61] 1.251408e-01 8.509241e-01 5.643887e-01 8.191023e-05 1.473345e-01
#> [66] 3.949991e-01 1.396471e-01 2.461836e-01 7.265306e-01 9.807610e-01
#> [71] 6.816967e-02 8.509241e-01 2.746192e-02 6.305861e-02 3.569594e-01
#> [76] 4.206091e-04 2.461836e-01 1.565468e-02 7.346037e-02 4.081506e-01
#> [81] 8.475059e-02 9.239470e-01 7.265306e-01 2.746192e-02 2.874662e-01
#> [86] 1.123026e-02 7.346037e-02 4.081506e-01 5.823680e-02 4.535644e-02
#> [91] 1.717173e-01 7.265306e-01 1.177296e-01 4.126586e-02 2.746192e-02
#> [96] 2.746192e-02 5.955577e-01 4.081506e-01 8.137370e-01 1.123026e-02
#> [101] 2.461836e-01 9.053307e-01 4.081506e-01 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 56 155 180 23 180.1 155.1 181 70 79 45 123 101 97
#> 12.21 13.08 14.82 16.92 14.82 13.08 16.46 7.38 16.23 17.42 13.00 9.97 19.14
#> 110 49 18 117 139 150 164 24 96 177 92 88 128
#> 17.56 12.19 15.21 17.46 21.49 20.33 23.60 23.89 14.54 12.53 22.92 18.37 20.35
#> 167 88.1 15 139.1 66 154 133 63 49.1 78 96.1 26 26.1
#> 15.55 18.37 22.68 21.49 22.13 12.63 14.65 22.77 12.19 23.88 14.54 15.77 15.77
#> 45.1 113 97.1 168 188 145 106 10 154.1 15.1 23.1 111 40
#> 17.42 22.86 19.14 23.72 16.16 10.07 16.67 10.53 12.63 22.68 16.92 17.45 18.00
#> 25 153 56.1 15.2 169 10.1 26.2 85 40.1 101.1 123.1 168.1 110.1
#> 6.32 21.33 12.21 22.68 22.41 10.53 15.77 16.44 18.00 9.97 13.00 23.72 17.56
#> 157 184 85.1 10.2 127 170 101.2 36 105 125 164.1 85.2 197
#> 15.10 17.77 16.44 10.53 3.53 19.54 9.97 21.19 19.75 15.65 23.60 16.44 21.60
#> 55 180.2 76 16 10.3 36.1 5 175 55.1 180.3 166 128.1 111.1
#> 19.34 14.82 19.22 8.71 10.53 21.19 16.43 21.91 19.34 14.82 19.98 20.35 17.45
#> 10.4 108 32 99 36.2 140 180.4 93 175.1 192 187 180.5 48
#> 10.53 18.29 20.90 21.19 21.19 12.68 14.82 10.33 21.91 16.44 9.92 14.82 24.00
#> 62 173 178 162 152 182 172 104 143 163 122 137 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 17 83 174 186 65 44 31 122.1 165 196 193 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 174.1 12 109.1 48.1 11 75 83.1 82 75.1 138 38 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 200 72 151 47 20 1 126 64 162.1 152.1 138.1 174.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 74 126.1 163.1 161 122.2 172.1 193.1 103 131 17.1 182.1 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 34 146 44.1 44.2 116.1 65.1 53 65.2 71 35.1 65.3 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 87 53.2 122.3 147.1 38.1 54 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[100]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002902015 0.176012519 0.713400099
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.336302479 0.002636607 -0.148652671
#> grade_iii, Cure model
#> 1.274812190
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55e4260bbbb0>
#>
#> $data
#> time status age grade_ii grade_iii
#> 100 16.07 1 60 0 0
#> 181 16.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 105 19.75 1 60 0 0
#> 66.1 22.13 1 53 0 0
#> 96 14.54 1 33 0 1
#> 199 19.81 1 NA 0 1
#> 45 17.42 1 54 0 1
#> 42 12.43 1 49 0 1
#> 93 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 79 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 124 9.73 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 107 11.18 1 54 1 0
#> 14 12.89 1 21 0 0
#> 25 6.32 1 34 1 0
#> 36 21.19 1 48 0 1
#> 8 18.43 1 32 0 0
#> 15 22.68 1 48 0 0
#> 76 19.22 1 54 0 1
#> 91 5.33 1 61 0 1
#> 153.1 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 93.1 10.33 1 52 0 1
#> 188 16.16 1 46 0 1
#> 88 18.37 1 47 0 0
#> 43 12.10 1 61 0 1
#> 90 20.94 1 50 0 1
#> 52 10.42 1 52 0 1
#> 110 17.56 1 65 0 1
#> 63 22.77 1 31 1 0
#> 113 22.86 1 34 0 0
#> 25.1 6.32 1 34 1 0
#> 88.1 18.37 1 47 0 0
#> 13 14.34 1 54 0 1
#> 117 17.46 1 26 0 1
#> 76.1 19.22 1 54 0 1
#> 57 14.46 1 45 0 1
#> 43.1 12.10 1 61 0 1
#> 26 15.77 1 49 0 1
#> 177 12.53 1 75 0 0
#> 15.1 22.68 1 48 0 0
#> 5 16.43 1 51 0 1
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 111 17.45 1 47 0 1
#> 197 21.60 1 69 1 0
#> 150 20.33 1 48 0 0
#> 134 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 101.1 9.97 1 10 0 1
#> 42.1 12.43 1 49 0 1
#> 5.1 16.43 1 51 0 1
#> 125 15.65 1 67 1 0
#> 58 19.34 1 39 0 0
#> 128 20.35 1 35 0 1
#> 128.1 20.35 1 35 0 1
#> 124.1 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 61 10.12 1 36 0 1
#> 81 14.06 1 34 0 0
#> 63.1 22.77 1 31 1 0
#> 49 12.19 1 48 1 0
#> 124.2 9.73 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 77 7.27 1 67 0 1
#> 179 18.63 1 42 0 0
#> 106 16.67 1 49 1 0
#> 88.2 18.37 1 47 0 0
#> 106.1 16.67 1 49 1 0
#> 194 22.40 1 38 0 1
#> 101.2 9.97 1 10 0 1
#> 32 20.90 1 37 1 0
#> 124.3 9.73 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 99 21.19 1 38 0 1
#> 199.1 19.81 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 55 19.34 1 69 0 1
#> 130 16.47 1 53 0 1
#> 68.1 20.62 1 44 0 0
#> 170 19.54 1 43 0 1
#> 155 13.08 1 26 0 0
#> 32.1 20.90 1 37 1 0
#> 124.4 9.73 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 188.1 16.16 1 46 0 1
#> 101.3 9.97 1 10 0 1
#> 134.1 17.81 1 47 1 0
#> 30 17.43 1 78 0 0
#> 68.2 20.62 1 44 0 0
#> 107.1 11.18 1 54 1 0
#> 56 12.21 1 60 0 0
#> 18 15.21 1 49 1 0
#> 105.1 19.75 1 60 0 0
#> 150.1 20.33 1 48 0 0
#> 110.1 17.56 1 65 0 1
#> 123.1 13.00 1 44 1 0
#> 194.1 22.40 1 38 0 1
#> 5.2 16.43 1 51 0 1
#> 129.1 23.41 1 53 1 0
#> 39.1 15.59 1 37 0 1
#> 24 23.89 1 38 0 0
#> 128.2 20.35 1 35 0 1
#> 50 10.02 1 NA 1 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 80.1 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 172 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 118.1 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 38.1 24.00 0 31 1 0
#> 118.2 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 12 24.00 0 63 0 0
#> 94 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 185 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 19 24.00 0 57 0 1
#> 142 24.00 0 53 0 0
#> 84.1 24.00 0 39 0 1
#> 165 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 138 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 34 24.00 0 36 0 0
#> 174 24.00 0 49 1 0
#> 120 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 182.1 24.00 0 35 0 0
#> 75 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 182.2 24.00 0 35 0 0
#> 176.1 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 135 24.00 0 58 1 0
#> 119 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 44.1 24.00 0 56 0 0
#> 122.1 24.00 0 66 0 0
#> 121.1 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 182.3 24.00 0 35 0 0
#> 84.2 24.00 0 39 0 1
#> 22.2 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 148.1 24.00 0 61 1 0
#> 80.2 24.00 0 41 0 0
#> 12.1 24.00 0 63 0 0
#> 186.1 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 174.1 24.00 0 49 1 0
#> 122.2 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 22.3 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 165.1 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 12.2 24.00 0 63 0 0
#> 146 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 186.2 24.00 0 45 1 0
#> 172.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 72.1 24.00 0 40 0 1
#> 151.1 24.00 0 42 0 0
#> 53 24.00 0 32 0 1
#> 186.3 24.00 0 45 1 0
#> 48.1 24.00 0 31 1 0
#> 121.2 24.00 0 57 1 0
#> 44.2 24.00 0 56 0 0
#> 44.3 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 21.1 24.00 0 47 0 0
#> 17.1 24.00 0 38 0 1
#> 126 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.336 NA NA NA
#> 2 age, Cure model 0.00264 NA NA NA
#> 3 grade_ii, Cure model -0.149 NA NA NA
#> 4 grade_iii, Cure model 1.27 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00290 NA NA NA
#> 2 grade_ii, Survival model 0.176 NA NA NA
#> 3 grade_iii, Survival model 0.713 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.336302 0.002637 -0.148653 1.274812
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 243.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.336302479 0.002636607 -0.148652671 1.274812190
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002902015 0.176012519 0.713400099
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.76639020 0.71702556 0.28361529 0.49334092 0.28361529 0.81334626
#> [7] 0.67906343 0.87097227 0.93201927 0.05729872 0.74555553 0.23840347
#> [13] 0.32529481 0.91998321 0.90792498 0.85826083 0.97777812 0.35165302
#> [19] 0.57819922 0.20530803 0.54227018 0.98897869 0.32529481 0.56038214
#> [25] 0.93201927 0.75263703 0.58708542 0.89580319 0.37565216 0.92602810
#> [31] 0.63875286 0.17140996 0.15232970 0.97777812 0.58708542 0.82636984
#> [37] 0.65507509 0.54227018 0.81989233 0.89580319 0.77328609 0.86462223
#> [43] 0.20530803 0.72443376 0.78688691 0.40990684 0.94959742 0.66316588
#> [49] 0.31137885 0.47312251 0.62179608 0.80673388 0.94959742 0.87097227
#> [55] 0.72443376 0.78009979 0.52327844 0.44293074 0.44293074 0.08937337
#> [61] 0.94375654 0.83277767 0.17140996 0.88960071 0.67906343 0.97214124
#> [67] 0.56929972 0.69435149 0.58708542 0.69435149 0.25539505 0.94959742
#> [73] 0.38733411 0.13300195 0.35165302 0.84557930 0.52327844 0.70951449
#> [79] 0.40990684 0.51340309 0.83918040 0.38733411 0.98897869 0.61317226
#> [85] 0.75263703 0.94959742 0.62179608 0.67112661 0.40990684 0.90792498
#> [91] 0.88338216 0.80011358 0.49334092 0.47312251 0.63875286 0.84557930
#> [97] 0.25539505 0.72443376 0.08937337 0.78688691 0.02339896 0.44293074
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 100 181 66 105 66.1 96 45 42 93 78 79 169 153
#> 16.07 16.46 22.13 19.75 22.13 14.54 17.42 12.43 10.33 23.88 16.23 22.41 21.33
#> 10 107 14 25 36 8 15 76 91 153.1 97 93.1 188
#> 10.53 11.18 12.89 6.32 21.19 18.43 22.68 19.22 5.33 21.33 19.14 10.33 16.16
#> 88 43 90 52 110 63 113 25.1 88.1 13 117 76.1 57
#> 18.37 12.10 20.94 10.42 17.56 22.77 22.86 6.32 18.37 14.34 17.46 19.22 14.46
#> 43.1 26 177 15.1 5 39 68 101 111 197 150 134 157
#> 12.10 15.77 12.53 22.68 16.43 15.59 20.62 9.97 17.45 21.60 20.33 17.81 15.10
#> 101.1 42.1 5.1 125 58 128 128.1 129 61 81 63.1 49 45.1
#> 9.97 12.43 16.43 15.65 19.34 20.35 20.35 23.41 10.12 14.06 22.77 12.19 17.42
#> 77 179 106 88.2 106.1 194 101.2 32 92 99 123 55 130
#> 7.27 18.63 16.67 18.37 16.67 22.40 9.97 20.90 22.92 21.19 13.00 19.34 16.47
#> 68.1 170 155 32.1 91.1 51 188.1 101.3 134.1 30 68.2 107.1 56
#> 20.62 19.54 13.08 20.90 5.33 18.23 16.16 9.97 17.81 17.43 20.62 11.18 12.21
#> 18 105.1 150.1 110.1 123.1 194.1 5.2 129.1 39.1 24 128.2 200 72
#> 15.21 19.75 20.33 17.56 13.00 22.40 16.43 23.41 15.59 23.89 20.35 24.00 24.00
#> 80 118 38 80.1 62 182 172 151 118.1 122 38.1 118.2 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 94 173 185 84 19 142 84.1 165 121 148 138 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 174 120 22 182.1 75 44 182.2 176.1 112 135 119 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 22.1 44.1 122.1 121.1 48 35 137 141 182.3 84.2 22.2 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 148.1 80.2 12.1 186.1 2 174.1 122.2 27 22.3 71 94.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 12.2 146 9 47 186.2 172.1 17 72.1 151.1 53 186.3 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.2 44.2 44.3 46 21.1 17.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 2
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>
#> $cure_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 0
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>